data mining project thesis

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3d face reconstruction using deep learning.

Student thesis : Master

Achieving Long Term Fairness through Curiosity Driven Reinforcement Learning: How intrinsic motivation influences fairness in algorithmic decision making

Activity recognition using deep learning in videos under clinical setting, a data cleaning assistant.

Student thesis : Bachelor

A Data Cleaning Assistant for Machine Learning

A deep learning approach for clustering a multi-class dataset, aerial imagery pixel-level segmentation, a framework for understanding business process remaining time predictions, a hybrid model for pedestrian motion prediction, algorithms for center-based trajectory clustering, allocation decision-making in service supply chain with deep reinforcement learning, analyzing policy gradient approaches towards rapid policy transfer, an empirical study on dynamic curriculum learning in information retrieval, an explainable approach to multi-contextual fake news detection, an exploration and evaluation of concept based interpretability methods as a measure of representation quality in neural networks, anomaly detection in image data sets using disentangled representations, anomaly detection in polysomnography signals using ai, anomaly detection in text data using deep generative models, anomaly detection on dynamic graph, anomaly detection on finite multivariate time series from semi-automated screwing applications, anomaly detection on multivariate time series using gans, anomaly detection on vibration data, application of p&id symbol detection and classification for generation of material take-off documents (mtos), applications of deep generative models to tokamak nuclear fusion, a similarity based meta-learning approach to building pipeline portfolios for automated machine learning, aspect-based few-shot learning, aspect-based few-shot learning, assessing bias and fairness in machine learning through a causal lens, assessing fairness in anomaly detection: a framework for developing a context-aware fairness tool to assess rule-based models, a study of an open-ended strategy for learning complex locomotion skills, a systematic determination of metrics for classification tasks in openml, a universally applicable emm framework, automated machine learning with gradient boosting and meta-learning, automated object recognition of solar panels in aerial photographs: a case study in the liander service area, automatic data cleaning, automatic scoring of short open-ended questions, automatic synthesis of machine learning pipelines consisting of pre-trained models for multimodal data, automating string encoding in automl, autoregressive neural networks to model electroencephalograpy signals, balancing efficiency and fairness on ride-hailing platforms via reinforcement learning, benchmarking audio deepfake detection, better clustering evaluation for the openml evaluation engine, bi-level pipeline optimization for scalable automl, block-sparse evolutionary training using weight momentum evolution: training methods for hardware efficient sparse neural networks, boolean matrix factorization and completion, bootstrap hypothesis tests for evaluating subgroup descriptions in exceptional model mining, bottom-up search: a distance-based search strategy for supervised local pattern mining on multi-dimensional target spaces, bridging the domain-gap in computer vision tasks, can time series forecasting be automated: a benchmark and analysis.

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data-mining

Here are 219 public repositories matching this topic..., theantimist / rs.

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hereismhtm / Association

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acdmammoths / ROhAN-code

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vojha-code / Anomaly-Detection

In data mining, anomaly detection (also outlier detection) is the identification of items, events or observations which do not conform to an expected pattern or other items in a dataset.

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minhhoangtcu / TCUDataMining

COSC 40023 for Spring 2017

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phung025 / orion

This repository contains the implmentation of a cluster-based outlier detection algorithm called Orion in Java.

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hereismhtm / Classification

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felixsteinke / DataMining-ArffGenerator

Computer Science - Semester 5. Project for Data Mining to create an ARFF file for the machine learning tool Weka.

• Updated Oct 31, 2021

AmiteshDTU / DST-ML-EkNN

This method is a solution to imbalanced data problem.

• Updated Jun 13, 2021

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Master thesis topics [closed]

I am looking for a thesis to complete my master, I am interested in Predictive Analytics in marketing, HR, management or financial subject, using Data Mining Application.

I have found a very interesting subject: "Predicting customer churn using decision tree" or either "Predicting employee turnover using decision tree", I looked around very hard but unfortunately couldn't find any relevant dataset to download ( Telecommunication Customer churn Dataset ).

I would like to work on a similar subject using "Decision Tree Technique".

Please suggest some topics or project that would make for a good masters thesis subject.

• data-mining
• predictive-modeling
• decision-trees

2 Answers 2

This is the approach I took:

• Find journals related to your field of studies
• Skim through the proceedings, see if there are titles that catch your interest
• Read the papers (carefully or globally) that seemed interesting
• Carefully consider the approaches and whatever future suggestions they present in their papers
• Think critically: What would you change? What do you want to find out? Don't limit yourself to data but rather orient from the perspective of research. Solutions for data might only become apparent when you know exactly what you want to examine.

I think this has advantages because these papers outline details regarding data as well -- perhaps you can use the same.

Present some papers and your idea to your prospective supervisor and he/she will make some suggestions. Researchers generally have a lot of knowledge about the possibilities and might even be curious about some things themselves.

Good luck! And enjoy.

First, talk to your thesis advisor before committing to a project. They know better than I do.

Secondly, just analyzing a new dataset using standard techniques doesn't make for a good masters thesis. Your project is expected to use some sort of novel approach.

With that said, I'd suggest that you start by reading up on existing decision tree techniques, learning why they work and what their flaws are, and try to find ways to overcome the flaws. Then, once you have your improvement, it should be relatively easy to find a dataset to apply it to.

Not the answer you're looking for? Browse other questions tagged data-mining predictive-modeling bigdata decision-trees research or ask your own question .

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14 Data Mining Projects With Source Code

Introduction, what is data mining, data mining projects for beginners, 1. housing price predictions, 2. smart health disease prediction using naive bayes, 3. online fake logo detection system, 4. color detection,  5. product and price comparing tool , data mining projects for intermediate, 6. handwritten digit recognition, 7. anime recommendation system, 8. mushroom classification project, 9. evaluating and analyzing global terrorism data , data mining projects for advanced, 10. image caption generator project, 11. movie recommendation system, 12. breast cancer detection, 13. solar power generation forecaster, 14. prediction of adult income based on census data, why are data mining projects so important, additional resources.

In today’s digital era, data has become the most important tool. All the computing processes right from the inception of collecting, tidying, analyzing, and finally interpreting it according to the business strategies is done on data. Every second, billions of data is generated to understand customers’ necessity for new offers, analysis of market risks and much more. With technological advancement, businesses and firms tend to follow data mining programs to develop all the future schemes.

The process of extracting the most useful information from lots of data to quickly identify all the present trends and patterns for businesses and huge firms to understand customers and make out important decisions is called Data Mining. In simple terminology, data mining is a way to recognize hidden patterns from the extracted information of the data required for the business with the help of data wrangling techniques to categorize important data stored in proper data warehouses with the help of data mining algorithms to generate maximum revenue for a business. Data mining, also known as knowledge discovery of data (KDD), uses highly complex mathematical algorithms for segregating data to evaluate the probability of the future decisions for the company’s business.

If you are planning to build your career in data mining, regardless of the fact that you are a student or a professional data analyst, it is always beneficial to have some outstanding data mining project ideas on hand. Not only building projects on data mining will help in building a strong portfolio, but also it will enhance skills.  

Confused about your next job?

Undeniably, data mining is an amazing career option and for that, following are outstanding data mining project ideas for beginners, intermediate and advanced students along with source code for additional help.

Let’s look at some data mining project examples for beginners.

In this data mining project, a housing dataset is used which includes all the prices of the different houses. In this project, the dataset for prediction of price is added along with location, size of the house, and additional information required for it. Depending on the level of sophistication, you can follow a predictive model with simple techniques such as regressions or machine learning libraries. The application of this project is in the real estate companies. This project utilizes algorithms and techniques for price predictions of the houses based on different housing datasets. Either you can carry out linear regression with a data analytics tool such as Tableau or Excel, or you can choose a machine learning library along with programming language “R” or Python.

Source Code: Housing Price Predictions  

Nowadays, medical care is something that anyone might need immediately, but unavailable due to various reasons. The smart health disease prediction is an end user support system that allows users to get guidance immediately with the help of an online intelligent health system. The system holds complete information about symptoms and the diseases associated with it. The system analyzes diseases associated with the symptoms for the patient and advises them for X-ray, blood test or CT scan as requested by the system. Users can also directly get in touch with the specialist doctors for any ailment and share your reports. It is not just one time, rather a proper login detail is shared for future use. 

Source Code –  Smart Health Disease Prediction

Each year, thousands of brands lose a huge portion of the sales due to unauthorized knock off brands and their counterfeits. These counterfeit products are made up of inferior quality and hence damage the credibility of the brand. Moreover, consumers feel cheated with their hard-earned money while shelling it out for just a mere counterfeit. Online fake logo detection system will distinguish between original product and forgeries for the consumers. Along with helping users to fight against the forged products, it also helps brands to combat piracy.

There are around 16 million colors according to different RGB color values, but a human mind can only remember quite a few. It is common that after seeing the color, you are still not able to name the color. In this data mining project, you are going to build an amazing app which is going to help in recognizing color from any image. All you need is a labeled data of available colors and then the program runs to evaluate which color resembles most with the selected color value and helps in detecting colors easily. You can use the Python programming language in which Codebrainz Color Names dataset will be used for the project.

Source Code: Color Detection  

With the increase in popularity of e-commerce portals, shopping websites are magnifying to a great extent to enable online shoppers to purchase anything with just one click and get it delivered at your doorstep. To purchase an item, people tend to spend quite a lot of time in searching a product and comparing it with other websites by themselves. In this project, you can compare product and price of a product to buy cheap and best deal available. Also, it will track consumer demand and inform when the commodity price is lowest and notify consumers proactively. 

Source Code: Price Comparing tool

Let’s look at some data mining project examples for intermediates.

One of the best data mining projects is the Handwritten Digit recognition project among the data scientists and all the machine learning enthusiasts. In this project, machine learning algorithms are used to distinguish and classify images of the digits written by hand. With the help of computer vision AI model, machine learning techniques and Convolutional Neural Networks, this project can be created which will have a nice graphical user interface to write or draw on the canvas and for the output a model is good to predict the digit. Python and R, both are good languages for this project. Python’s Scikit-learn model using algorithms such as K-Nearest Neighbors and a Support Vector Classifier will be apt for the project.

Source Code:  Handwritten Digit recognition  

Looking out for  data mining projects with source code?  The Anime Recommendation system is one of the best projects as it includes a data set containing information regarding user preference from 73,516 users on 12,294 anime. Every user in the database will be able to add anime to the list and share ratings compiling a data set with those ratings. Anime recommendation system project helps in creating a system that produces efficient data based on the user viewing history and sharing rating.

Source Code:  Anime Recommendation System  

In this data mining project, details of the samples related to the 23 species of gilled mushrooms from the Lepiota and Agaricus Family of Mushrooms available in the Audubon Society Field Guide to North American Mushrooms (1981). Each mushroom variety is categorized as edible, poisonous, unknown edibility or not recommended. So, in this project you will be able to distinguish mushrooms from the respective group although there is no rule “leaflets three, let it be” to define if it is edible or not.

Source Code:   Mushroom Classification

Terrorism has mushroomed due to its deep roots at certain locations of the world. With increase in its activities, it is important to stop its spread or analyze the global terrorism data to identify the terrorist activities. Internet plays a major role in spreading terrorism by way of videos and speeches among youth to join the terrorist organizations. This project will help in detecting, evaluating, and analyzing global terrorism data and flag them for human review. Data mining helps in scanning and mining from all the unorganized and unstructured pages or data available that promotes terrorism and flag them. 

Source Code:  Evaluating and Analyzing Global Terrorism Data 

Let’s look at some data mining project examples for advanced learners.

In this interesting data mining project, image is an easy and memorable task for human beings, but for computers just a bunch of numbers for each pixel of color value. In this project, the most difficult task for the computer is to understand the image and then generate the description of it. If you are planning to go with Python programming language, Keras framework would be perfect with Flickr 8K data set.

Source Code – Image Caption Generator

Top-Notch companies such as Amazon or Netflix use this system to recommend their customers with the movies in their database. To design this movie recommendation project, you can choose any one approach out of two. First option is a content-based filter in which the system finds some similarity around different projects in terms of features or attributes that could be actor, genre or director of the movie. Another option is collaborative filtering that compares tastes of two accounts and suggests based on the user ratings. This system helps companies to engage their customers to the respective platforms. You can use MovieLens dataset if opting to go with the R programming language.

Source Code:  Movie Recommendation System  

Data mining projects hold a special place in medical contributions. In this project, breast cancer is detected using the Python programming language. In this IDC_regular dataset helps in detecting actual presence of the commonest form of breast cancer i.e., Invasive Ductal Carcinoma. In this form of cancer, it targets milk ducts invading the fibrous or fatty breast tissue outside the duct. If you want to build this project using Python language, you should use Keras library for classification and IDC_regular dataset.

Source Code:  Breast Cancer Detection  

With the help of extracted data from two solar power plants over a period of 34- days, two pairs of files are available. Each pair includes one power generation dataset, and another is sensor reading dataset. In the power generation dataset, each inverter extracts information which has several lines of solar panels connected to it. An array of sensors optimally located at the plant collects the sensor data. In this project, you will be able to get answers of the amount of power generated in a month, any faulty performing equipment in the plant or panel cleaning/ maintenance update.

In this project, the dataset is evaluated based on a transparent open box (TOB) network for data mining and predictions. It provides accurate information from the hourly data record from power generation dataset and sensor reading dataset.

The following project is the classification project to predict the income level of an individual that exceeds 50K based on the census data available at the repository. The dataset that is used in the projects are variables such as age, type of work, working hours, sex and many more. It helps in understanding the standard of living of the city, benefit of setting up the business or bank loan eligibility. Also, it helps in understanding the real estate preferences by average income of the people residing in the area. In this project, you will also be able to figure out the type of tourist places that people from other countries would like to travel.  

Source Code:  Adult Census Income Level Prediction

In this data-centric world, data mining projects hold great importance in everyday life. It provides us a reliable source of resolving tough problems and different issues in this challenging world. Some of the benefits are: –

• With the help of new and legacy systems, data mining helps in making well-informed decisions.
• It offers cost-effective solutions compared to other applications designed with other technologies.
• It helps data scientists to deal with huge amounts of data and scrutinize the essential data out of it.
• It makes businesses make profitable production and operational adjustments according to the demand.

To cut the long story short, data mining is the process of analyzing huge chunks of data to discover business intelligence which helps in solving problems, seizing new opportunities, and mitigating long term risks. The process of discovering useful patterns and relationships in large volumes of data helps in understanding a problem deeply and tactics to deal with it diligently. It is widely used in research, medical, business and security to turn large data into useful information. Get started from the above list of projects from beginner to advanced and sharpen your skills. These data mining projects with source code will help in learning new abilities.

How do you create a data mining project?

To create a data mining project, follow these steps

• Understand business and project’s objective
• Understand the problem deeply and collect data from proper sources.
• Cluster the essential data to resolve the business problem.
• Prepare the model using algorithms to ascertain data patterns.
• Evaluate the data according to the business goal or to find a remedy for the problem.
• Last, deploy the solution and get the results to make decisions.

What are the 3 types of data mining?

The 3 types of data mining are

• Hypothesis testing
• Directed data mining
• Undirected data mining

What tools are used in data mining?

Top tools used in data mining are

• Rapid Miner
• Oracle Data Mining
• IBM SPSS Modeler

  What are different tasks associated with data mining?

The following activities are performed for data mining.

• Classification
• Association Rule Discovery
• Sequential Pattern Discovery
• Deviation Detection

Data mining is a process of analyzing big data and creating business intelligence decisions. You can pick data mining projects to strengthen your skills and climb the success ladder. Whether you are a beginner, intermediate or advanced learner, this list will help you in proving your mettle.

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How to choose a good thesis topic in Data Mining?

I have seen many people asking for help in data mining forums and on other websites about how to choose a good thesis topic in data mining .  Therefore, in this this post, I will address this question .

The first thing to consider is whether you want to design/improve data mining techniques , apply data mining techniques or do both.   Personally, I think that designing or improving data mining techniques is more challenging than using already existing techniques.  Moreover, you can make a more fundamental contribution if you work on improving data mining techniques instead of applying them. However, you need to be aware that improving data mining techniques may require better algorithmic and/or mathematics skills.

The second thing to consider is what kind of techniques you want to apply or design/improve? Data mining is a broad field consisting of many techniques such as neural networks, association rule mining algorithms, clustering and outlier detection. You should try to get some overview of the different techniques to see what you are more interested in. To get a rough overview of the field, you could read some introduction books on data mining such as the book by Tan, Steinbach & Kumar ( Introduction to data mining ) or read websites and articles related to data mining. If your goal is just to apply data mining techniques to achieve some other purpose (e.g. analysing cancer data) but you don’t know which one yet, you could skip this question.

The third thing to consider is  which problems you want to solve or what you want to improve.   This requires more thoughts.  A good way is to look at recent good data mining conferences  (KDD, ICDM, PKDD, PAKDD, ADMA, DAWAK, etc.) and journals (TKDE, TKDD, KAIS, etc.), or to attend conferences, if possible, and talk with other researchers.  This helps to see what are the current popular topics and what kind of problems researchers are currently trying to solve.  It does not mean that you need to work on the most popular topic. Working on a popular topic (e.g. social network mining) has several advantages. It is easier to get grants or in some case to get your papers accepted in special issues, workshops, etc. However, there are  also some “older” topics that are also interesting even if they are not the current flavor of the day. Actually, the most important is that you find a topic that you like and will enjoy working on it for perhaps a few years of your life. Finding a good problem to work on can require to read several articles to understand what are the limitations of current techniques and decide what can be improved.  So don’t worry. It is normal that it takes time to find a more specific topic.

Fourth,  one should not forget that helping to choose a thesis topic is also the job of the professor that supervise the Master or Ph.D Students . Therefore, if you are looking for a thesis topic , it is good to talk with your supervisor and ask for suggestions. He should help you.  If you don’t have a supervisor yet, then  try to get a rough idea of what you like, and try to meet/discuss with professors that could become your supervisors. Some of them will perhaps have some research projects and ideas that they could give  you if you work with them. Choosing a supervisor is a very important and strategic decision that every graduate student has to make.  For more information about choosing a supervisor, you can read this post : How to choose a research advisor for M.Sc. / Ph.D ?

Lastly, I would like to discuss the common question   “ please give me a Ph.D. topic in data mining “, that I read on websites and that I sometimes receive in my e-mails. There are two problems with this question. The first problem is that it is too general . As mentioned, data mining is a very broad field. For example, I could suggest you some very specific topics such as detecting outliers in imbalanced stock market data or to optimize the memory efficiency of subgraph mining algorithms for community detection in social networks. But will you like it? It is best to choose something by yourself that you like. The second problem with the above question is that choosing a topic is the work that a researcher should do or learn to do. In fact, in research, it is equally important to be able to find a good research problem as it is to find a good solution . Therefore, I highly recommend to try to find a research topic by yourself, as it is important to develop this skill to become a successful researcher. If you are a student, when searching for a topic, you can ask your research advisor to guide you.

Also, just for fun, here is a Ph.D thesis title generator .

If you like this blog, you can subscribe to the RSS Feed or my Twitter account ( https://twitter.com/philfv ) to get notified about future blog posts.

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482 responses to how to choose a good thesis topic in data mining.

Good article.

i need your guidence to select a topic for research in data mining area????

Then, I suggest to read the blog post on top of this page. It provides guidance about how to search a topic.

thank you for your guidelines

Really good one….

Sir, i want to do Ph.D on data mining but i am not a good programmer so please tell me the topic of research on data mining or any other area which need no programming skills.

plz take it urgent. Hoping for your reply at the earliest.

If you want absolutely NO programming and still do some data mining, then I think that you would have to go toward mathematics and statistics. Or you could do some applied data mining. For example, you use some already made data mining tools or software such as Matlab or R to analyze some data. The contribution would be to do something new with the data instead of proposing new algorithms.

For finding a specific topic, you can read the blog post above which explain the steps for finding a good topic.

i am interested in page ranking topic for my mtech thesis in data mining. Can you suggest me some sources from where i can get good information about the topic?

I don’t work on this topic. So just using Google Scholar could be a good idea.

Hiee mam can I get ur mail I’d I want to discuss for thesis

Yes Sir, Mr. Mohd Shahid Khan said right for those who can not do programming and the same problem with me also so please suggest those topics through which I can do my project in data mining in M-Tech as you said in his reply that “use some already made data mining tools or software such as Matlab or R to analyze some data. ” So please suggest me on this type of topic.

The goal of this blog post is to explain how to search for a topic, rather than give topic. It takes time to find a good topic, so I cannot do it for you. But you can read the blog post to understand how to search.

HI. I want to do a Ph.D. in statistical data mining. But it is difficult to choose a topic. There are too many data mining topics. I’m thinking of improving decision tree mining algorithms with statistical validity tests. Is it a good idea?

I’m not working with decision trees, but it seems like an interesting topic. What is important is that you will propose something new that has not done before and that is useful. I think that it could meet these criteria. I would recommend to read about what has been done on statistical validity tests with decision tree, to try to see what can be done. Note that, even if you choose this as your project, it is possible to change the orientation of your research later on.

Hope this helps,

Many people have already worked on extending statistics to various types of classifiers. Try to do research on Ensemble classifiers and other types. As you are interested in decision trees, I suggest you to look at the usage of emerging patterns.

Sir, i want to do Ph.D on data mining but i am unable to find any problem in data mining so please tell me the problems on data mining or any other areas. plz take it urgent. Hoping for your reply at the earliest

Data mining is very broad. I could give you some topics, for example, what about applying neural networks to recognize music, using association rules to classify medical data, improving the memory efficiency of clustering algorithms, sequential pattern mining algorithms, etc. I mean, I could suggest you a lot of topics like that. But data mining is a very broad field. It would be better that you like. Do you have any specific interests in data mining?

I am looking for a research topic within data mining. I read your this reply and I am interested in neural Networks. Please suggest me a topic and where to start looking for it ?

Thanks & Best Regards, Jyoti

If you are interested in neural networks, then I see two possibilities: improving neural networks or using the neural networks in new ways…

I’m not an expert on neural networks so i don’t know what are the current research issues on this topic. I would recommend to read the titles and abstract of articles from conferences and journals on neural networks such as http://www.ijcnn2013.org/ and http://www.icann2013.org/ http://delab.csd.auth.gr/eann2013/about%20eann%202013.php You could also search on google scholar for recent articles to get some pdf.

This will give you some ideas about what is the current popular topics related to neural networks. Then you need to find one that you like.

If you have chosen your supervisor already, I think that you should also discuss that with your supervisor.

Hi Jyoti I am interested in this topic Maybe we can help each other [email protected]

hello sir ,

Am willing to do research in data mining, can you suggest a good topics in data mining

I have answered this question in the blog post at the top of this page.

sir i m interested in data mining .but i feel troublin choosing my research topic kindly suggest me topik i shal b grate ful to u thanks

You should read the blog post on top of this page. It explains how to find a topic.

my area of interest is medical data mining can you please suggest some topic on it ?

No. I don’t work on medical data mining.

I am looking for a research topic within data mining in Big data. Please suggest me a topic and where to start looking for it ?

Thanks & Best Regards, arvind

Did you read the blog post?

sir, i would like to work on the concpt of audio and video streaming in dataminig. which topic will suitable for me for resarch. Please suggest the topic,

I’m not familiar with the topic of audio and video streams. You would need to do some literature review to know what people have done on this topic.

“Philippe Fournier-Viger”u r saying iam not familiar in this and that plzz mention in post in which area you are familiar

If you want to know about my areas of research you can have a look at my webpage: http://www.philippe-fournier-viger.com

Sir, iam seraching for a thesis topic in Data Mining for my M.Tech course. I select Cloud Mining but in this topic what i have to do i dont know. Please suggest me.

Thanks & Regards

In cloud mining, you could write some parallel data mining algorithms that can run on the Map Reduce framework. This is just an idea. There is certainly many other topics on cloud mining.

Thanks for the good articles. I want to do research on Data Mining Applications to Agricultural Field topic( I feel this interesting topic as of now). What would be the best topics on this. How to approach to these? Is that could be a good idea or not?

Yes, i think it can be good idea. I’m not familiar with agricultural field so I cannot tell you what are the best topics related to this. But you can find this out by doing a literature review. What you could do is to find a problem that people in the agricultural field have and then to see what data mining technique can be applied and what are the limitations. Then, if you could extend the data mining technique to address the limitation, it would be great.

Thanks Philippe for quick reply. I am reading all your articles and will follow them. Mean while understand the data mining algorithms using your suggestions(books,from open source software, etc). Try to implement small algorithms and get confidence…. Will contact you If I need a suggestions. Thanks

Hello Sir, I am Student of M Tech(CSE) and i want to do research on data mining and mine area of Interest in “Web Usage Mining and Social Network Mining”.Can u suggest me Certain topic regarding this Mining Area……

It is a good area, especially social network mining, because it is popular, right now. But to find a specific topic in this area, I cannot help you. You need to do a literature review.

Hello sir can I get ur mail I’d . sir I want to discuss in this

Hello sir, I like to do research in data mining sir but I do no what to do? And how to do? Please help me.. my guide is asking me research topic. I do no anything.. pls help me to find good topic sir in data mining or please tel me any nice topic. I do no what current process is going on data mining sir…

Its very ugent sir please help me pls..

thank u sir…

If you had read the blog post, I wrote that the question “please give me a topic in data mining” is too general. You should first learn about what is data mining and what are your interests in data mining because data mining is a very broad field. If you just ask for a topic in data mining, then I could suggest you any random topic such as: improving the memory efficiency of frequent subgraph mining algorithms for the case of uncertain data with applications in social networks. But will you like it? I think that it is better that yo u find a topic that you like. In the blog post, I gave the information about how to find a good topic.

Thanks sir,

And suppose i am selecting the Social Network Mining as a My Research Topic can u tell me for the Implementation purpose which Programming lang. or the tool is required? is there any specific Web Site from which i can get the Source Code

I do not work on social network analysis so I cannot help you too much. I know that some social network datasets are available on the web such as the DBLP dataset. There is some datasets here for example: http://snap.stanford.edu/data/ You can also find more by searching on Google.

I know that there is a conference called ASONAM about social network mining. You could check what is published there to get some ideas of what researchers do on this topic and there is some journals about social network mining such as this : http://www.journals.elsevier.com/social-networks/

For the programming language, I think that you can use anything you like. However speed is sometimes important in data mining. So I would not choose a language like PHP that is considered slow. Personally, I would use a language like C++, Java of C#, because they have good performance. But it may depends on what you do…

For source code, I don’t know. You would need to search.

hello sir.,

In ‘improving the memory efficiency of frequent subgraph mining algorithms for the case of uncertain data with applications in social networks’ its already researched sir you can see in this website… http://dl.acm.org/citation.cfm?id=1646028

thany u…

It is not a problem if someone has already worked on a topic. You can do something differently or better.

By the way, I just gave this topic as an example.

Very helpful post. I’ve somehow managed to choose a topic but I don’t know weather it’s a good topic to continue on my Ph.D or not. I’m masters student and I’m working on “online microbloging/social networks’ stream mining”. I want to know your opinion on this topic as an expert in data mining domain.

I think that it is a good topic. Social network and micro-blogging are popular research areas, right now, and it is good to choose something that is popular. Stream mining is also an interesting topic because it is more difficult than mining a static database.

Hi Philippe , A very Big thank for this article , It helps me lot . I m interested in “using association rules to classify medical data” , will you please give me more specific idea , in which way I could do research for this topic . how can I improve already exist research work in this topic.

I think it can be a good topic. In my opinion, for this kind of topic, you can have two contributions: (1) a contribution is mining the medical data to do something useful and (2) the second contribution is maybe improve some association rule mining algorithm so that it work better with your data.

It would be important to find some medical dataset for your project. Would it be patient record? datasets about drugs ? datasets about genetic data? datasets about diseases? etc. I don’t know. You would need to search for some data. You could have a look at what is available on internet. Or you could also see with your supervisor if you can obtain some medical data at your university if there is a medicine department. Ideally, you could collaborate with some people working in the medicine department that could help you about understanding medical data in your project and tell you what is important..

After you got your data and you know what is the goal that you want to do with your data, you could apply association rule mining and see what are the problems that you have with the current algorithms. Then, you could find some way to improve them so that they better suit your data and what you want to do with the data. For example, maybe you find that current algorithm cannot do X. Then you find a way to modify it to do X, whatever X is. Or if you find that association rule is not the best solution, then you can use something else.

For improving algorithms, you would need to understand the current algorithm and see what they cannot do for your medical data.

Thanks Philippe

hello sir can u suggest me some topic regarding “Frequent Pattern Mining”

I like to do research in healthcare using data mining.

please give me more specific idea about this topic.

You can make two kinds of contributions: – contribution about doing news things with the healthcare data by applying data mining algorithms – creating some new data mining algorithms or techniques that are better than existing techniques or deal with specific problems in healthcare data.

For more specific topics, I cannot help you because i’m not a specialist in healthcare. Furthermore, I gave the steps in the blog post about how to search for a good thesis topic in data mining.

hello sir, i am searching for the m.phil thesis topic in datamining and give some idea about the thesis paper.

You could start by reading the blog post above. In the last paragraph, I mention that the question “give me a topic in data mining” is too general.

sir i want to do research in data mining in the field of clustering please mention any new suggestions on this topic

Clustering is good. But you need to find something more specific. For example: improve the speed or memory usage of some clustering algorithms? modify the algorithms to handle new types of data? use the algorithms to perform something better? propose some new ways to detect outliers in clusters? …. I just say that as examples. You would need to do a literature review to know what is a good topic and what has been done in clustering (I don’t work in this sub area of data mining).

Sir, i want to prepare a journal on data mining.its a part of our syllabus.so could you please suggest one topic on data mining. take it urgent. Hoping for your reply at the earliest Thanku

Respected sir, I am Mtech student and m going for resarch in data mining…my guide says for selecting a particular field like data mining or cloud mining .sir plz suggest me which is best..

Data mining or cloud computing? I think that both are ok and popular in the industry. So to choose one depends on what you like.

sir if i select one from both data mining and cloud mining plz give your idea…….

You could design a new data mining algorithms that can run on the Hadoop technology for cloud computing. It could be a clustering algorithm, a pattern mining algorithm, a classification algorithm… or something else. Then when you design an algorithm, you need to show that it is faster, more memory efficient or that it performs new things that no other algorithm can do, or be used to do something new. If you do a literature review, you should be able to find a good topic.

sir what can i say to guide data mining or cloud mining………

As I said in the blog post, you should do a literature review so see what has been done and what can be done. This, you need to do it by yourself.

hi what about opinion mining? is it good topic for master thesis?

It is a good topic. I think that there should be many interesting challenges related to opinion mining. It could be challenges specific to a language (e.g. French, Spanish, etc.) or a specific type of opinions (political, etc.), or some technical challenges (improving the accuracy), etc.

thanks. is there a software for opinion mining? for example i know clementaine for data mining.

Maybe. But I don’t work on this topic so I’m not aware of this.

what about data mining in cancer, diabets and heart disease data? are they good? or they are old?

There are certainly some things to do on these topics (you would need to do a literature review to see what has been done recently). For medical topic,s a challenge is to obtain medical data and find a specialist that could guide you about what the data means and what would be important to do with this data. If you can have access to medical data (maybe that there are some on the web too), it could be great.

sir i want to start mtech thesis in cloud mining or web mining sir plz suggest me any suggestion………..

I suggest to read articles from recent conferences on these topics to see what has been done recently. This will help you to choose a topic.

Hello sir, the subject of my thesis is the prediction of links in social networks. What is your opinion and do you can help me with some ideas.

I don’t know much about social network mining. If you want to know what is the latest research on this topic, you would need to do a literature review (search for articles on this topic in recent conferences/journals).

first of all i would like to give my thanks for the article. It is really vry helpful for new researchers . I want to do Phd in “Data Mining on e-learning ” plz suggest me some research topic on it.

You should look at recent conferences about data mining & e-learning to see what are the current topics and see if there is something that you like. For example: EDM, AIED, ITS, ICALT, EC-TEL etc.

Thanks for excellent support to researchers, my topic is privacy preservation in data mining. Is topic is good to work on? can u pls. suggest some problems on this topic. I am interested in consumer behavior and dental field. thanks in advance..

Privacy preservation is definitely an important topic, since more and more data are collected about individuals or other sensitive topics and it is important to protect it. For the challenges, and finding a good specific topic, the only way to find out is to do a literature review (read recent recent articles on privacy preservation to see what other researchers have done on this topic recently). Me, I don’t work on this topic, so I don’t know what is the latest research on this topic.

Thanks for your help sir..

Its great that science doesn’t require any boundary..

Thanks for your expertise.

You are welcome! 😉

Hi Philippe , A very Big thank for this article , It helps me lot . I m interested in “using association rules to classify medical data” , will you please give me more specific idea , in which way I could do research for this topic . how can I improve already exist research work in this topic.

You could: (1) improve association rule mining algorithms (2) apply them in novel ways on medical data or to perform something better by using association rules (3) do both (1) and (2).

But you need to define more precisely what you want to do with medical data and what kind of medical data. Personally, I have no knowledge about medical data. The only way to find out is to read articles on this topic or to find some expert from the medical domain who could guide you about what is challenging in the medical domain. Also, maybe you can check if someone has done a similar topic before and identifies what are the limitations of their work. This could be a starting point.

You could also start by searching for medical data because you need data if you want to do data mining! Depending on the data that you can get and what you want to do with the data, it may gives you some hint about what are the problems with the current association rule mining algorithm for this task and what could be improved.

Hello sir, I like to do research in data mining sir but I do no what to do? And how to do? Please help me..

As I said in the blog post, data mining is a very broad field. If you don’t know what you like in data mining, then perhaps that you need to read about data mining first (e.g. an introductory book), or read articles from recent data mining conferences and see if there is a topic that you like.

sir i have to choose a topic in data mining for thesis in mtech having to read this blog i got topic which i like are using association rules to classify medical data so suggest me how initiate work on this

I have answered this question already. You can read my answer, two messages above this one.

Hello sir, I like to do research in data mining sir but I do no what to do? And how to do? Please help me.. my guide is asking me research topic. I do no anything.. pls help me to find good topic sir in data mining or please tel me any nice topic. I do no what current process is going on data mining sir…i hv no knowledge of programming more.

As I said in the blog post, I will not answer the general question of “give me a topic in data mining”, as data mining is a very broad field and I will not do a literature review for you to find a good up-to-date topic. I suggest first reading about what is data mining and then to look at recent papers published in data mining conferences and choose something that look interesting .

Hi   If I want to do data mining using fuzzy logic, can you help me

You need to define your topic more clearly. Fuzzy logic is a technique for representing fuzzy things. But then, what you want to do with fuzzy logic? You want to apply this to what kind of data? Why you want to apply fuzzy logic to this data? What is your goal?

sir i m doing research in cloud plz suggest me any area or artical or topic.

You need to read articles from recent conferences to see what people have done on this topic recently, as I explained in the blog post. This will give you ideas about what is interesting for this topic.

Hi I have great interest in data mining. but my professor field is not data mining. but I want work on data mining. Will you please help me in this regard. or suggest me person that work on data mining. I’ll give you the final results. I hope you can help me

Maybe try to find another professor at your university that is working on data mining?

hi i am M.tech student i want to do dissertation in data mining my interest to do research in security in cloud computing with data mining can you pls suggest better topic or any idea about data mining in cloud computing pls give me quick reply its very urgent!!!!!!! pls…….. thanx

As I said in the blog post, I suggest reading recent articles related to your topic in recent data mining conferences/journals to see what is popular right now and find a topic that you like.

Hi ankita , I see that you post this almost a year ago and i have the same interests in my research. So how was it!? and what suggestions you may kindly offer to enhance my proposal.

many thanks dear. Firas M.A

Hi Philippe,

Fantastic website, Recently I’ve started my 4th year of college and have chosen data mining as an elective. Im looking into the major challenges faces in adopting data mining techniques within the public and private sectors. Just wondering could you steer me in the right direction.

Many thanks, Colm

Thanks. I’m glad that you appreciate the website.

I’m into the technical aspect of data mining. I’m a professor in Computer Science. What I do is that I design some data mining algorithms and we apply them in some research projects. I don’t work closely with the public/private sectors since I’m working on the fundamental aspects of data mining (algorithms). So I cannot give you a lot of information about the challenges for adoption of data mining techniques.

Some challenges that come to my mind are: – you need some trained people to understand what is data mining and how to analyze the data (e.g. data scientist) – data mining techniques offered in data mining software are not always well-suited to all domains. All data mining software offers a limited choice of data mining techniques. If they don’t fit with what the company wants then you perhaps need to hire some data mining specialist to design something custom. -…. Philippe

Fantastic, That’s a great start none the less. I appreciate your reply. Thank you again.

sir m doin a research on Research issues on web data mining is this a good topic… i have read the introductory part nd some pdf also what else i can do in that in order to make my research better.

Yes, web data mining should be a good topic. Then, I think that you need to continue reading on this topic. By reading on the topic, you will see what people have done recently and get some ideas about what you can improve or do differently. It is important to know what other people have done before starting to do a research project.

I’m MSc student interested in data mining for my thesis. I have got a good approach how to do my thesis. Your suggestion is valuable. My thematic area is weather forecasting, what do you help me in identifying specific title. It is urgent! Thank you very much

This is great information, thanks’ for share!

Dear Sir/Madam

I am pursuing M.Tech(CSE), I want do project in data mining, and also same project need to PhD thesis after MTech. Shall you give me good research topic on data mining? Please reply me Thank you

You can read the last paragraph of the blog post starting with “Lastly…”. It answers this question.

i need to make my thesis in data mining using cluster algorithm for web pages to make semantic web

I have choosen mood identification from music data as my topic.its a part of multimedia data mining.so i want to research using data mining algorithm.so can you give me suggestion on this topic.

thank you sir.

sir, i want to do research in data mining for my m.phil. how can i find a topic for my research or give some topics for suggesstion. or any website/book i can refer pls give that address/bookname

thnks in advance

You can start by reading the blog post.

hi sir, i want to do my mtech theisis on clustering or classification. can u suggest any new topic in this field???????????? thank you sir

your type of article should be encouraged in research development. the article has directed my path on how I can come up with a researchable topics. I will still call on you after following your laid down approach to data mining. thank you Sir

Glad that you like the article and that it is helpful.

I want to do my PhD work for privacy preserving in data mining for various transactions.Suppose I purchased items among a b c d e f g h 1 0 1 0 1 1 01 . 1 means I purchased that particular item and 0 means not purchased.Which kind of technique I can apply in to protect binary data.I think the Privacy can be protected by using some cryptography algorithm.I am little bit confused how I can implement my idea with these binary transactions. please help.

Yes, I think that you can encrypt your data using an encryption algorithm.

The fact that the transaction is binary or text should not make any problem for an encryption algorithm. In any case, you will give data to the algorithm who will generate encrypted data.

To know how to do it in a particular language such as Java, etc. you would need to see what are the encryption algorithms available and search for some tutorials, I think.

i m doing thesis in cloud mining secuirty,sir plz suggest me any important topic………

I think that you need to define your topic more clearly. Cloud mining is a too broad topic. You need to make a literature review to see what is interesting in this area or discuss with your research advisor. Me, I don’t work in this area of data mining and I will not do the literature review for you 😉

Hello. I’m a Business Analytics (M.Sc.) student. I would like to write my thesis about a specific problem on business data which can be solved by a data mining algorithm. I like the kind of problems from the Data Mining Cup. I can not decide on any specific algorithm right now but I know that the problem should be business oriented. I would be thankful for any advice.

sir i am an assistant professor in comp. aplications. i am interested to do a research in agricultural field especially in cardamom cultivation. it would be helpful if you suggest some related topics to the starting of the work

Hi Your opinion do we work on the subject ‘ data mining based constraint’

What is “data mining based constraint”? Data mining with constraints? This seems too broad. I think you need to define topic more clearly.

Sir, I m interested in “using association rules to classify medical data”, but i am not so good in programming.Is it possible for me to continue this topics without programming or is the source code available in the web site? if source code is needed , will you able to provide me some links for source code?

There are some source code for association rule mining such as my own data mining library: http://www.philippe-fournier-viger.com/spmf/

However, if you want to make a Ph.D. in Computer Science you will most likely need to do programming because doing a Ph.D. or Master degree in Computer Science without doing programming does not make sense, I think.

Another possibility is to do a thesis from a mathematic perspective if you don’t want to do programming.

hello sir special thanks for the article. sorry if it is also includes in the “can’t be answered ” questions. I would like to do my Ms thesis regarding Social network analysis, I do some research but I can’t decide yet ,which filed: could you suggest me some more conference or journals regarding this topic despite from http://asonam.cpsc.ucalgary.ca/ and http://www.journals.elsevier.com/social-networks/ which you already mentioned or any other way to extract open areas in this field.

thank you so much regards,

I don’t work on this topic so I cannot help you much. To answer this question, I would need to search just like you would do.

Sir, i have to work on “finding closed frequent patterns and their association rules” on data mining, i’ve tried but cant find better approach to work with, so please tell me some parameters and approaches that can improve the efficiency. thanks

If I had a very good idea about this I would keep it for myself as I also work on pattern mining 😉 There are certainly some ideas but it takes time to find a good idea and when you got a good idea is better to keep it for your own research. If you cannot find one, then you can consider variations of the problem of association rule or itemset mining. For exampple, if you consider uncertain itemsets, fuzzy association rules, etc. etc., then maybe these topics are less explored and it is easier to find some ideas. This is just some thoughts. In my opinion, it is easier to create a new problem or a new algorithm for a variations of the problem of association rule mining than to try to make something faster than the best algorithms for association rule mining.

can you please tell me few research topics on fuzzy multimedia data mining related topics

Hello Sir, I’m interested in Big data. 1. How does data mining and Big data are related ? 2. I scanned the internet for Big data architecture, i cant get clear picture of it. Can u suggest me a standard article or book for understanding Big data ? 3. how to develop a own architecture for large data handling ?

Sir, can you please tell me the research topics in data mining for m.tech thesis. i am not good at programming.

Did you read the blog post? It explains how to search for a topic.

Sir,I need some topics which have less programming to do as a project.please suggest me some ideas.

Please read the blog post carefully. It explains how to search for a topic.

sir! give me some idea that what new can i do for “feature subset selection” in data mining….

I don’t work on this topic.

Sir, Im dng Mtech my research area is datacube Materialization & MapReducing.. can you gve some suggessions for me..

I would simply suggest to apply the advices that I gave in the blog post.

Really good. Many thanks to Mr.Philippe for his replies.

i am searching Ph.D research topic in privacy preserving data mining

Did you found your topic

Sir, May I get data set for doing my research on “data mining for elearning” pl repy.

You may find some by searching on the web or you may record your own data if you have some e-learning system at your university. There also exist some educational data repository like PSLC datashop: https://pslcdatashop.web.cmu.edu/ But personnally I would prefer to generate my own data than to use the data from someone else.

Sir, I am doing M.Tech in Computer science and technology. i want to do final project on data mining but i am unable to find any problem in data mining so please tell me the problems on data mining or any other areas. please take it urgent. I look forward for hearing good response. Thank you. Neeta Jadhav

This blog post explains how to choose a topic in data mining. That is the point of this blog post. Have you read it?

sir, I m student of Mtech and I am not able to find topic for my thesis can you suggest me some interesting topics.

The whole point of this blog post is to explain how to search for a topic. I suggest to read it. Moreover, as I wrote in the blog post, I will not answer this question.

Sir, I am seraching for a thesis topic in Data Mining for my M.Tech course.

can you suggest me some recent topics, I m not able to find any topic. just suggest me some topic so that I can start reading about it.

memory efficiency of clustering algorithms, is this topic is good.

I think it can be a good topic.

But you would still need to search a little bit to see what has been done already.

I am doing an undergrad research on multimedia mining can you suggest a topic?

No sorry. Looking for a topic takes time. You need to do a literature review to see what has been done before. I cannot do this for you.

Hello sir, I’m doing my thesis on closed frequent patterns and association rules, i am trying to find it by combining “n-list” and “charm” , So, how can i use any frequent pattern finding structure to find closed patterns, or is it possible. Any guidance plz….. Thanks,

There are many ways to solve the problem of closed itemset mining. Several algorithms have been published. To my knowledge, LCM should be one of the fastest according to the last FIMI competition in 2004. Other fast algorithms are DCI_Closed, FPClose, Charm etc. So, yes there are certainly still possibilities to improve these algorithms.

How to do it ? I would say to read recent articles to see advances or ideas in that could be transposed to closed itemset mining. Or to try to find new ideas. However many research have been done on this topic. To make a significant contribution on this topic one would preferably need to compare his new algorithm with the fastest closed itemset mining algorithm.

About nList, I have briefly read about it and it seems to be another variation of the FP-Tree. Therefore, perhaps that it would be easier to use it with FPClose than Charm…. I don’t know. Besides, I have noticed that the author of nlist seems to be posting links to his own article on many internet forums including on my own forum several times. I had checked the paper but I was personally not convinced by the experiments.

sir, i want to work on data mining in cloud computing? can u suggest me any appropriate topics related to this field. balvinder taneja

I would suggest to apply the recommendations that I wrote in the blog post on top of this page.

Sir, I am seraching for a thesis topic for my M.Tech course. can you suggest me some recent topics, I m not able to find any topic. just suggest me some topic so that I can start reading about it. n my area of interest is network security or data mining

As I said in the blog post, I will not suggest any topics. Looking for a topic takes time and I don’t have time to search for topics for other people. Moreover, as I explained in the blog post, you should choose a topic that you like, not a topic that someone else has chosen for you.

If you have no idea what to do about data mining and network security, then a good start is to search for papers about data mining and network security in Google Scholar to see what other people have been doing on this topic.

Really nice article , I just want some research topics using clustering

Hello Sir, I am very glad to know that someone is guiding the humanity in some way, like you through such a honestly interesting page. Sir i am searching for my thesis topic ……..but after studing your kind blog and following your steps I am going to do my research in obtaining a data about earth properties and their environment and materials condition and based on that data i am going to know that to some extent that in this place there is occuring that ratio of iron , gold water etc.. Is this will be good for me . Need your kind reply. thanks in advance.

Hello, Thanks. Seems like a good topic to me. But you would still need to see what other people have done before to see what you can do differently or improve.

thanks sir plz help me in this i will inform you daily…

sir, what possible topics can i do if i like to work on text mining i want to do a research that can be use to our school can you suggest some ideas ?

plz reply thanks mr.phillipe

As explained in the blog post, to find a good topic, you should do a literature review. It takes time and I cannot do this for you.

I want researches about applying Data Mining techniques on master and PHD thesis and dissertations database. Thanks.

You can use tools like Google Scholar to search for articles.

Sir i want to do my mtech thesis on page ranking algorithm in data mining. Please suggest me some good topic in this for my thesis.

The blog post explains how to search for a topic. Did you read it ?

Firstly, I would thank you for useful article, then I am interested in clustering techniques for Data mining. Please guide me a topic for my PhD dissertation. My email is [email protected] thank you.

Hi, As explained in the blog post, I would suggest you to do a literature review on this topic to find out what has been done recently on clustering. You can start by searching on Google Scholar to find some recent articles on clustering and to see what are the current challenges.

Best regards,

I am doing my research work in recommender systems (Data mining area) and concentrating attack concept. Now i am seeking classification, clustering algorithm. which one is the best and how to proceed?

I have no idea what is “concentrating attack”. I think it depends on what you want to do. Classification is generally to classify instances in a set of predefined categories. Clustering is generally to automatically create categories. So they don’t exactly do the same thing.

i have decided to do my thesis on focused web crawlers for gathering educational material on the web. i just wanted to know if this topic is relevant in today’s time , i hope it not a very old topic?

I think it is ok. It depends on how you do it. You need to read articles on this topic to see what has been done already on this topic. I personally don’t know what has been done on this topic. Depending on what has been done, to make a good research work you need to improve or bring some new ideas. If you can do that on that topic, than the topic should be good.

Hi, I am looking for a research topic within data mining. I am interested in multimedia data mining in social media with social event detection as an application. My problem is to find a gap and a topic for my thesis. Please suggest me a topic and where to start looking for it? Best Regards, Sam

As I said in the blog post, looking for a topic takes time. You need to look for it by yourself or ask help from your research advisor. If you have no idea where to start, then I suggest to just search the keywords that you know in Google Scholar to find some articles or look for some general survey articles perhaps to get an idea about the whole domain first. Then when you find something interesting, look deeper.

Hi I am a Phd student of medical datamining but Im still trying to identify my research questions … I am looking on applying datamining algorithms on clinical datasets as i dont have strong programming skills…could you please suggest any new applicable methods that is yet to be explored as my possible reseach questions?

Thanks, Hope to hear from u soonest!

I don’t have time to search for you.

hello I like to do datamining on blood transfusion data plz guide me how I can define subject about it

Hi Philippe

It is truly astonishing to see how many ‘graduate’ students completely misread your post! I stumbled on this post during my own search for masters ideas, and I guess I got my night’s entertainment too.

Good post, and I applaud your patience.

Hi Francois,

Thanks. 🙂 I now have the proof that someone has read the whole blog post 😉

I read your blog too and I also translate and put it on my website to help thousands of students who are concerning about their topics!

Great job. Thank you very much!

That is great. If you translate the content word by word, then please cite the original website as the source of the text.

Hi, thanks about your recommendations they are so help full. can you plz recommend some topics about outliers in data mining. I read all of the comments but i could not find any related things . is it some topic that common or it was old and have not any new thing for research. thanks alote philip.

If a research area become less popular, it does not mean that there is nothing interesting to do. There are always some research problems. You just need to find one.

For specific topics, I recommend to follow the steps in the blog post, which starts by doing a litterature review.

hi sir can you please tell me related topics on Analytical hierarchy process in data mining for Ph.D. Please give me more specific idea about this topic. Plz reply s soon as possible

Hello, I don’t work on this topic. You would need to do a litterature review as explained in the blog post.

Hello sir, I have to give a research proposal for M.phil in computer science. can you please suggest me some brief review type of research topic in neural networks(extensible).

No. I don’t have time to do it.

Sir i want to relate data mining in agriculture.. but i’m unable to find any specific thing. plz guide me for my PhD topic selection

As said in the blog post, you need to do a literature review and/or ask your supervisor to help you.

I want to do my research in data mining…

please sir can I apply any data mining technique on DIP..

or to develop any data mining technique for image processing…

I don’t work on image processing but there are certainly some way to apply data mining on images.

For example, there are some works on spatial association rule mining to find patterns in geographical data. This geographical data could be extracted from satellite image before applying the data mining algorithm. This is just an example. You would need to search to find more information about the possibilities.

data mining have different technique like svm ,ANN , PCA, decision Tree ,rough set theory, clustering that are mostly used for DIP

Hi If i can use current method of text mining for another language, for example English method for Arabic, would it be a new challenge for my thesis and write a new article? Arabic language is different from English, so by using current method in different langue i can achieve new result.

From a data mining perspective, it is a new challenge, if the method do not work well with Arabic and you need to modify the method to make it work for Arabic. If the method just work for arabic without modifying it, it would seem too simple, perhaps. But text mining is not my specialty. You may have a look at papers about text mining for other languages to see how they have presented their work.

Hi It is about a year that a write a comment here :). On that time I choose opinion mining as my thesis topic. I work hard to fine a new approach in opinion mining. But you know, I was not so successful in this way. I make a new sentiwordnet for a new language from existing wordnet. but I couldn’t suggest a new method. some one told me, that by combing existing method I can introduce new one. but how can i do that ? for example by combing svm and naive bayes how can i create a new method? really I need your help. how can I continue my thesis in a way to find a new idea? thanks

hi hello , im student of MTECH 1st year and want to do reseach in data mining , by which i can easily take admission in phd programe .. so tell me topic which have wide scope of research ?

I really need more help into the research of mining and what questions I should research more on it is due tomorrow and I do not know anything

I need help to answer the questions I am a year 12 pa student from international overseas

Sir, can you please help me, i am searching for PHD research topic, i am thinking for context aware computing in mobile computing.is it a good topic to move on?

I don’t work on this topic. It sounds ok but you need to do a literature review and maybe make it more specific.

hi,i need help i must impelementation this paper with c# but i dont know how do ?plz help me

A Novel Method for Privacy Preserving in Association Rule Mining Based on Genetic Algorithms Mohammad Naderi Dehkordi Ph.D Student, Science & Research Branch, Islamic Azad University (IAU) Department of Computer Engineering, Tehran, Iran

I cannot help you.

Yes good article i really like it i will find out how we can improve better library services though data mining i will also try to learn it

Any management related data mining topic for MSc thesis? I don’t have much algorithm related knowledge , got programming knowledge in c/c++/sql.Please provide me some recent topic relatd to management related .

To find a recent topic, you need to do a litterature review or talk to your supervisor. There is no way around it.

dear sir i am too much confused that what topic for thesis should i select. if you have any good topic so plz guide me thanx .

if i want to do thesis in datamining first thing i need is the data sampel. but in our country people donot give any data.. then can you give me solution for findind the data samples for datamining thesis.

Then, you may have to collect your own data or to use public data from another country if there is some available. There are many websites that you can find using Google that offers public datasets that you can download. If you are lucky, there will be some public datasets.

Otherwise, depending on your topic, you could consider generating some artificial datasets but it may not be a good idea depending on your project. In general, it is recommended to use public data.

can you say me how can i collect the data sets required for datamining because it is impossible in the country like nepal..

How to collect the data depends on what kind of data you want to collect.

For example, if you are doing data mining on network data, then if you have access to a webserver or router, you could just use the logs from the server or router to perform data mining. Another example is if you are doing data mining on source code from software. You could just download any open-source project and perform data mining on the source code.

On the other hand, for some types of data, it may be very difficult to collect data. For example, if you want to do data mining on medical records, it may be very difficult to get access to that kind of data from the government, unless some public data is already available.

it was very usefull article. thanks so much:-)

Thanks yr bog provides very important guidelines. sir I want to do Ph D in Data Mining. I read yr blog & from that i decided to do work in Data Mining on Medical Data(gynec or orthopedic). I can get database of patient, diseases etc as one of the my family members is a doctor. so pls could you tell me what can i do after getting a database.

It is good that you have data, but what is your goal ? what do you want to do with the data? Do you want to perform early prediction of who will get a particular disease? do you want to predict what will be the reactioon of a patient to some drug prescription? etc. You need to decide what you will do with the data. To do that, you should have a look at what other people have done by reading some articles on this topic.

Thanks for reply Sir i wanted to predict the baby born date and prediction of premature delivery. so can do , how to do

You would need to have some training data. Then you could train a neural network to do the task of prediction. Similar techniques to neural networks may also be used like SVM…

after selecting data how to select algorithm or method

In general, it is recommended to try the popular methods first. To know what is the popular methods for your topic, sometimes it is necessary to read articles on the topic. In your case, you could try neural networks directly I think. If it does not work well, then you would need to find something else by reading. Or sometimes in data mining, we even need to modify the algorithms to achieve what we want if there is no algorithms that are appropriate for what we want to do.

Hello sir, I am pursuing mtech. I have chosen opinion mining under data mining. Can you suggest some topics in it? Can you suggest which tool I should learn? I am free for 2 months. I want to utilize this free time in doing something productive in topic. So can u please help me ?? Thank you

As said in the blog post, you should do a litterature review, which means to read articles on your topic (opinion mining). This will allows you to find some topics. I cannot do that for you.

hello sir, i am willing to do research on data mining field, i have decided some topics like data mining techiniqs for online social networks and analysis, web mining for predicting user behaviours , topic detection and tracking .. out of them which one is suitable or how can i combine all these issues..

These topics are are quite general, so any of them would be ok. But in any case, you will need to define your project more precisely. And to do that, the only way is by reading papers on these topics and try to get some new ideas about what could be done better or differently, or what has not been done yet. To do this takes time, and you need to do it by yourself or with your the help of your supervisor.

I will be try for Phd in Psychological data & Data mining concept but my work that analysis of mind traffic. Psychological or spiritual concept & data mining Concept combined for research work &Is it contribution of Computer Engineering? suppose yes then please tell me right way……………….

Yes, it can be. It is definitely possible and interesting to combine Computer Science with other disciplines such as Psychology. Now, whether it deserves a Ph.D in computer engineering depends on whether you will be solely a user of the software of someone else or you will develop your own software program that solves non trivial computer science problems with respect to your application. You may also want to check previous thesis published at your university to see examples of Ph.D thesis subjects that have been accepted as PhD thesis.

Thanks for guideline…………….

dear sir i am completed mphil too much confused that what topic for thesis should i select. if you have any good topic so plz guide me thanx .

As I said in the blog post, I will not provide topics. But I explain how to search for a topic.

sir i am interested in data mining in educational or learning field for my m.tech dissertation can u give me some specific ideas abt it???

Data mining in educational or learning field is still a very broad topic. You need to define something more precise.

You could search papers in Educational Data Mining (EDM) and Learning Analytics communities (LAK) for papers on these topics. Or also in some e-learning related journals and conferences.

sir for decision support in dental disease prediction which kind of further research i can do for masters can u give me some idea about this ?

i need your guidence .. to choose my thesis topic on data mining

The blog post on this page explains how to choose a topic.

Sir, I was choose datamining for my phd. 2 years over.but still i did not choose proble. but my dataset is medical imbalanced liver data dataset. It’s correct or not .how to choose problem based on this things and how. please help me.

I think you should discuss with your research advisor to ask for some help in choosing your problem. I cannot give you any ideas since I don’t work on medical data and choosing a problem takes time. Actually, what you probably need is a medical expert that can tell you what are the important problems in the medical field that you could solve. Otherwise, you could have a look at related papers and see what other people have published on this type of data.

Sir, I was choose datamining for my phd. 2 years over.but still i did not choose proble. but., my minor project topic is TECHNOLOGY AND ITS IMPACT IN THE CLASSROOM. i think continue this topic . pls help related to data mining or big data. It’s correct or not .how to choose problem based on this things and how. please help me.

another question big data is new one. to choose related to the topic in TECHNOLOGY AND ITS IMPACT IN THE CLASSROOM. pls help

Hi, technology & impact in the classroom looks like an important topic for the society.

If you want to do data mining related to this, as I have described in this blog post, you will need to read research papers on this topic and to find something that has not been done before or that you think you can do better. I cannot help you to do this because it takes time to read papers. But you can ask your research advisor for help.

Another important point in data mining is that you will need data for your research, either by downloading it or by collecting your own data. Since the availability of data may have an influence on what you can do for your topic, you could also search on the web or ask authors of papers if they can provide their data, if you plan to use the data of someone else rather than collecting your own data.

Sir, i would like to do a Masters dissertation on the topic data mining in Automotive Diagnostics. Could you please suggest me some topics

For data mining, you need some data to do the mining. Can you obtain a database of automative diagnostics. If yes, then you could try to build a system that may automatically diagnose what is the problem of a car based on what he learned from the database. That is just an idea. I don’t work on this topic and I did not do a literature review. So it does not mean it is a good idea. As I said in the blog post, what you should do first is a literature review.

Sir I want to do Ph.d in Database. I have knowledge of Batch programming. But i am unable to find that how can i choose topic for research and how i use database and batch programming combination in research area?

Please help me.

In my opinion, if you want to do a Ph.D in computer science, you need to know some programming language like C++ or Java. If you only know batch programming (such as .bat files), it seems hard to do a Ph.D. in computer science.

Sir i have good knowledge of database also. i have done my internship in oracle. and i am very interested to do ph.d in database. but i am confused to choose a topic for research.

As explained in the blog post on top of this page, choosing a topic takes time, and you need to do it by yourself or with the help of your PhD supervisor. Basically, it requires to read recent papers to find what is popular topics now and think about some ideas or something that has not been done.

Sir can i choose “Data Mining Automation Process” topic for research area in Ph.d?

Helo sir, now i’m doing my m.phil computer scince, please give idea to select the topic in data mining area,

You can start by reading the blog post on top of this page. It gives you the steps to find a good topic rather than giving you a topic because finding a topic takes time and thus I cannot do it for other people.

And also need some research paper using clustering, now I’m interested to do my project in mat lab so give topic to related to using mat lab

hello sir, i have chosen “stock price prediction using machine learning algorithms” as my project topic…and i got information from my senior that we need to consider the stocks of america or London as Indian stock market is not so strong and we can’t get much data..but i don’t know from where i can get stock data for mining..and how can i access data and make use of it for mining in my project…please guide me from where can i get stock details of these countries stock market and how to mine that data??

I have not worked with stock data before. But usually, here are the ways to get data for a data mining project: – Find some data that have been collected by other researchers . If you read some papers that have used stocked data, they may indiciate that the data is available on their webpage. In that case, you can download it directly. If its not, you may contact the authors of the paper directly by e-mail and ask them for their data. You may tell them that you will cite their paper if you use their data. – Collect your own data . You could write a small program such as a web crawler to browse some website that offers stock data and collect it by yourself. – Check some dataset repository. There also may be some webpages that are datasets repository such as the UCI repository that offer many datasets. You may check them. But I don’t think that there are stock data on UCI, for example.

If you collect your down data, the advantage is that you will have all the data that you want. But you will spend more time to collect the data.

If you use the dataset of someone else, then, you may not have all the information that you want, because the other researchers may just have collected the information that he needed for their research.

hi….. really good one. this page especially helped me a lot as i am in my initial days for selecting my research topics this helped me alot like how to start? where to start? i am really thankfull to the advisor.

You are welcome!

Dear Philippe Fournier-Viger I have real benefitted from your blog. Most appreciated, it has real enlightened me on choosing my MSc research proposal.

Nevertheless, how do i write aproposal to be approved by the panel. Kind regards, Thaddeus

I’m glad that the blog has been interesting for you. Thanks for your feedback!

Hi Philippe Fournier-Viger I am a beginner in data mining. As i am going to carried out my Ph.D in data mining applied in bioinformatics. I am really confused how to start my work.

I really thank prof.Philippe Fournier-Viger for replies and help .

sir i want to choose a research topic in data mining sir what can i do for choosing a research sir i need those topic which are so sample and are not complex sir plz say me today

hello sir, i did my M.Sc research on enhanced data mining algorithm on online Electronic shopping please i want to some topics related to this for my PhD research works.

I cannot search a topic for you because it takes time to find a good topic. But you may read the blog post on top of this page which explains how to search.

Hello sir, I need your guidance to choose topic in conferrence,So sir please give ideas about some recent problems in data mining, and how to solve it?

I only have time to search topics for my own students. The goal of this blog post is to explain how to search so that you can do it by yourself.

sir,my topic is “stock market prediction using machine learning algorithm”, first thanks for your idea regarding collecting data from the different sources, sir now i am planning to use any machine learning algorithm in prediction and not understanding among SVM,ANN and K-Nearest Neighbour techniques which will be more suitable for stock prediction?? please do help

hello sir, i have chosen “opinion mining” as my project topic, my question is what is new”hot” areas. i know some topic like: 1. opinion mining classification 2. opinion extraction 3. opinion search and retrieved 4. opinion spam detection 5. quality of reviews 6. lexicon generation i am interesting on recommendation system based on opinion mining . how about that and please suggest me new areas . my 2 ed q is how to find a real problem ???

Since I don’t work on opinion mining, I’m not aware of the recent topics in this area. You could find some ideas by reading the recent papers in conferences on data mining, AI or recommendation system (e.g. RecSys), or journals. I see that you have done some litterature review already. Then, you should continue reading 😉

thank you prof Philippe Fournier for your guidelines, my second question is how to find a real problem ?

I’m not sure what you mean by “real”. I guess that you mean important problem with real world applications. If this is what you mean, then well, there is different way to find interesting problems to solve. One way is to read papers and see what are the problem solved by other people. Then you may define the problem slightly differently than what they are doing. Or you can use their problem and propose a better solution to their problem. Or if you want to find some ideas of problems that are more applied, you may talk with expert in the industry, etc.

I really have to commend you Philippe for continuing to respond to comments over a year and a half later! This blog post was very helpful. I have already been reading quite a bit of literature and I am running into the problem of having too many interests. I just have to focus on one and go with it. Thanks!

Hi, Thanks. Glad it is helpful.

Hi I wrote a comment but there was no answer 🙂 I write it again. Hi It is about a year that a write a comment here :). On that time I choose opinion mining as my thesis topic. I work hard to fine a new approach in opinion mining. But you know, I was not so successful in this way. I make a new sentiwordnet for a new language from existing wordnet. but I couldn’t suggest a new method. some one told me, that by combing existing method I can introduce new one. but how can i do that ? for example by combing svm and naive bayes how can i create a new method? really I need your help. how can I continue my thesis in a way to find a new idea? thanks

Hi, sorry for not answering you the first time. I have been a little bit busy recently. First, thank you for coming back to this website! Doing research is hard… it is not always easy to find new ideas. That is true. Sometimes, it may takes times to find something interesting. Or sometimes, we may have a new idea but if may fails or provide bad results. This is normal. The more you do research, the easier it will get. Yes, it is possible to combine two methods to get a new method. But it should make sense to combine the two methods. We should not just combine two methods for combining two methods. For example, combining naive bayes and SVM may not make sense depending on what you are doing. Also, combining two methods does not mean that you will get better results. Moreover, if you combine two methods, but the combination is straightforward, then maybe that it is not a significant contribution because it may be too simple.

If you are working on a new language, then you may try to find what challenges are specific to this language. If you can identify some new challenges for your target language than you may find a way to adress these specific challenges and it could be your contribution.

I just talk in general because i don’t work on opinion mining. But don’t worry. If you work hard enough you should find some new ideas.

thanks. But sometimes I become hopeless. I think maybe opinion mining a research area that there I cant continue it because the are so many research about it and is not possible to find a new method.

kindly suggest me the topic for research on data mining so i can start my theses on data mining.

thanks & regards amit kumar

Hello Professor Philippe

I am Nishat Undergraduate Final Year Student. I would like to do my undergraduate thesis on Data Mining. I have read several article on it still I am little bit confused about it. However, I would like to do my thesis on Data Mining specifically on Social Networking site like – facebook or twitter. However, I need your suggestions how to start working on them. It would be really great if you could provide me some suggestions. I am looking forward to hear from you.

Hi, Thanks for commenting on this blog post. My suggestions: – read papers about social network mining to know what other researchers are doing. In your thesis, you need to do something that other people did not do yet or do something better (faster, more accurate) than what they are doing. So you need to know what they are doing. – you will also need to find data. Either you try to collect your own data. Then you should try to work with the API provided b;y twitter etc. to see what you can collect. or you can try to find some public datasets or contact authors of other papers to get their data. This s important because you need data to do your research and dependng on what your data contains you may or may not be able to do some research project related to social network mining. Best,

Dear Professor Philippe

Thank You for your Kind Suggestions.It shows me a way to start work on my thesis.

So to start with, im helping my friend to find good reference in finding the thesis topic. she kind interested in school related topic sir. can you suggest me anything or give me a little hint as milestone maybe, i would really appreciate it. thanks

Then she may like e-learning topics. If she is interested in data mining, she could check “educational data mining” and choose some specific topics in that area.

I am student in computer scince . I would like to do my undergraduate thesis on Data Mining , I want to use wireshark to collect data from intranet (small lan (univercity))and track the movement about ip and protocols and use data mining tools to know types of protocols and IPs and content of massages, I need your suggestions how to start working on them. It would be really great if you could provide me some suggestions. I am looking forward to hear from you.

Thanks for message. I cannot help you too much since i’m not working on this topic. But the most important in a data mining project is always to have data. You may try to collect some data to see the feasability. Besides, what is even most important is to read what other people have done about applying data mining or machine learning techniques to analyse network data. There are some people who have work on this topic before. You need to read at least briefly their paper to see what they have done. This is important because in research, it is expected that you will do something new that other people did not do, or something better than what other people did.

Hi, I have a data-set of 1000 feature. I use svm and naive bayes for classification. I use present-absent and TFIDF for them. but the result is different. how can I find the reason of this difference? I want to know why svm and NB got different result and why using different feature cause different too.

there are 1000 feature and I cant examine them one by one its correlation. is there a method for that?

Different techniques gives different results. Why is a difficult question to answer. You may need to make several experiments with your data to find out why. And as you said, with 1000 features, it may be complicated. But have you tried to use some techniques to reduce the number of dimensions like PCA? Or you could just do some pre-processing to remove some attributes and perform some tests to see the results. Just some ideas.

thanks, but by using PCA only the number of feature decreased, but I cant understand which features have more effect on the performance of classification. can you you guide me which experiment should I do to understand the reason?

Ok. If you have a target attribute X and you want to know which attributes A1, A2… Am is more important with respect to X, then what about just calculating the Pearson colleration between each attribute and X?

yes, but I think calculation is not logical and it is time consuming.

If you want to know if two attributes are corelated, calculating the correlation or covariance are very good ways to get an answer.

You can write a short program that make a loop over all your attributes and calculate the correlation of each of them to the target attribute. Then you just run it and you will see which attributes are more correlated to the target attribute.

This is not time consuming. And why it would not be “logical”?

OK, thanks. I should write a program to calculate it.

Sir, I am doing M.tech( CSE).. I want to do my research on Proactive risk management on banking delivery channels (i.e ATM , net-banking , mobile- banking etc) can i use Data Mining for this?? or plz suggest me sm data mining technique or tool, which i can use to analyze banking data

I’m not much familiar with banking. But data mining can be used on any kind of data. So there should not be any problem.

Maybe classifications algorithms like neural networks, SVM etc. could be a good technique if you want for example to classify the customers as at risk or low risk.

Hello prof Philippe,

I’ll be starting my PhD. Topic which i have selected is “Improving existing data mining algo for big data on mapreduce ” what do you think about this topic? Can you give me any suggestions?

It looks like a good general topic since big data is popular and map reduce is a popular technology. But it is still a little bit too general maybe. What kind of algorithms? What do you want to improve? Maybe you could be more specific. If you want to improve clustering algorihtms, then you could say that in your topic. Or if you want to improve something else, then you could say it.

Hi, I came across your blog while I was searching for articles to refine my area of research which is data mining. The post is very helpful. Since data mining is sort of a new area for me and I am reading on data mining in Manufacturing and Operations Management. My aim is to optimize the production process to keep one of the the raw material (fuel) cost at minimum. I have collected 10 years of daily records and I would be pleased if you could suggest on how I can approach this from your expertise.

I am not familiar with this kind of problem. It seems like an optimization problem. In artificial intelligence, genetic algorithm, ant colony algorithm etc, may be used for optimizations problems, but i’m not sure that it would fit your problem.

Thanks Philippe your blog is very helpful. I did Msc computer sc and I want my PHD Topic to focus on improving data mining techniques for Big data. I am apply for PHD and I dont have a supervisor yet. So far I have been familiarizing myself with several data mining algorithms but because of time can you guide me somehow on data mining techniques whose improvement can be good for big data analysis.

Thanks for your comment on the blog. I cannot recommend much about that because data mining is very broad. With respect to big data, you could improve any kind of algorithms: clustering, pattern mining, classification, stream mining, outlier detection, etc. etc. In other words, most topics in data mining can be combined with big data. So you should choose something that you like. I would just recommend to continue reading and try to focus on a topic that you like.

ok. Thanks.

Hi sir, I came across your blog while I was searching for articles on data mining. This is really a kind contribution.. I have planned to do work on Educational data mining, i will get students data including social and economic attributes and then find their effects on grades, finally suggest some ways of improving grades. I want to know is this enough for an MS thesis or some thing more should be done???? I have also seen some other researchers done same work but mine data set and attributes will be different. Please give me some kind suggestion..

Hi,I am searching about topic for thesis of phd on the other hand, I love datamining with .may you help me how can these fields combine together , many professors said to me that not can define the topic in level of phd about datamining please guide me

It takes time to find a topic. I cannot do it for you. You can read the blog post on top of this page that explain how to do it.

hello sir..really a nice article.. i am doing my masters in computer science and for my thesis i am interested in data mining and specially in web mining….. as i was starting from a scratch this helped me a lot… thank you…..

truly helpful article for beginners …starting from the scratch

I’m an undergraduate.I hope to do my final year research in data mining.I think to do identify hidden purchase pattern of hotels customers through the data mining.sir,can you give some advices to successful my research?

Hi Sir please tell me what is the missing on text mining topics related to Arabic language. I’m really confused about selecting my master topic. I have read about Ontology and summarization topics but until now the idea or the topic title is now clear for me. So, kindly please guide me on my research topic with respect of Arabic language text mining and NLP techniques. Thanks,,,

Hi. Sorry, I cannot find a topic for you.

Your Blog is very good for young researcher. I am working on frequent pattern mining. Can you suggest from where I got quality work related to this topic. Thanking you

Hi, thanks. I would recommend to look at the papers published in top conferences: KDD, PKDD, PAKDD, ICDM, CIKM, ADMA, etc. and also published in top journals: TKDE, TKDD, DMKDD, etc. You may find many papers on Google Scholar. I would say try to look at what the people have been doing recently to find something that you can do.

Sir i want prepare one journal on data mining..its a part of our syllabus..so could u please suggest one topic on data mining..and also the procedure for preparing a journal. Thank you

I don’t know what you want. You can take any topic if you don’t care…. classification, clustering, pattern mining. Whatever you like.

I have to prepare one research paper.I had gone through some research papers related to data mining in health domain. Sir I was wondering if you could possibly suggest one topic on data mining in health domain.

Sorry but I don’t work in the health domain. Moreover, as said in the blog post, finding a good topic takes time.

Thank you sir for your replies.Please continue the same in future also. I am doing ph.d and want to do research in clustering. Kindly guide me.I want to do on medical data.

My area has ben changed now as my Guide is changed. he told me to look for “Big data and web mining”. I have only one month to prepare the synopsis… Should I go in Content web mining or usage web mining. Which one is easier to work with? I want to take social networking sites for this. Will it be fine?

Kindly Guide me.. Regards

Don’t know which one is easier. Web mining is a popular topic, so it should be fine. But to do data mining you need to get some data. For social networks, there a website call SNAP that gives some datasets. https://snap.stanford.edu/data/

I m Farhad and working as a DWH Engg and my skill set is ETL, Oracle SQL,PL/SQL, Teradata and Unix.

so can you please suggest the topic in DWH, I know ETL very well.

current working in eBay for e-commerce project.

No, I cannot suggest any topic. It takes time to find a good research topic. You may follow the step in the blog post.

Hi,I am searching about topic for thesis of phd on the other hand, I love datamining with .may you help me how can these fields combine together ,memory efficiency of frequent subgraph mining algorithms for the case of uncertain data with applications in social network is it correct or not.if it is corrctet how to get the information about the problem tell me suggestion .thanq.

You need to read the papers on topic to know if someone has already done that or not and to know if you like the topic or not. I did not read much on this topic so I cannot tell you. But if you like subgraph mining, then, you can find some problems in this area. To find papers, just search on Google or Google Scholar and read it.

For a MS thesis, the requirements depends on the university. Some university may have lower or higher requirements. The topic looks interesting but you may discuss with your supervisor to know if it is enough. If someone has done it before it is not so original but if you can show something new in it, it would be better.

Thanks sir..

Greetings of the Day!

Was searching for topic for my thesis on Data Mining and came across this site. Very useful indeed. 🙂

I have been able to get transnational data of ATM of a bank which I got with recommendation from my college for the sole thesis purpose only.

Basically, I want my Thesis report could suggest bank’s manager to predict how much Money is necessary to be kept in ATM Vault for a particular day as more money kept is no good.

Now I want your suggestion whether I should stick to only One Algorithm and find the solution Or Should I analyze various Prediction Algorithms and find the best one among them?

As being an Average Joe, I have to research and get into with numerous algorithms and techniques for comparative analysis of algorithms and afraid i miss my thesis deadline as well.

Lastly, if anything else can be done with this transaction data apart from vault cash prediction, please suggest me so that I can think other aspects as well for my thesis.

Looking forward for positive response.

I would suggest to first start with an algorithm to get a first solution. Then, after that you can see if you can improve the work by using different algorithms. But before starting with a first algorithm you still need to read a little bit to choose that algorithm well.

Other topic? Yes certainly. You could for example, try to find the optimal moment for refilling the ATM with more cash. Should we fill it everyday in the morning ? or … ? I think that you may find other variations of this problem.

Thank you for your valuable suggestion.

Hello sir…Thank you for this blog post. I am new in data mining and and i find this field very interesting and want to do my thesis in this but unfortunately i am not getting any support from anywhere.I have learnt about all algorithms in theory and now i am planning to work on missing value imputation but i am not sure about is it a good field to proceed. I am not getting help from anywhere. Any of your suggestion would be of great help to me. Thank you.

My advice: try to look at recent research on this topic. If there are recent research on this topic in good conferences/journals, then it is a good topic. Otherwise, it may be an older topic. But there are certainly some challenges to solve. My final advice: work hard. The topic is important but how hard you work is also important to do good research.

Thank you sir.

i am kasthuri. How will i select a research topic in data mining?

You can read the blog post on top of this page.

i am kasthuri. How will i select a good research topic in data mining?

What about reading the blog post on top of this page?

I wish to my part time time ph.d in data mining. give some ideas about how to choose research topics

Did you read the blog post on top of this page?

Hello Sir , i need your help I am doing master of computer Engineering i want list of topic in data mining for dissertation.Please help me as soon as possible . Thank You Vikas

No. I won’t do that. Searching for a topics takes a time. You need to do it by yourself.

hello sir.. good afternoon… i have some confusion about selecting area of data mining. i like data mining but some people told me that data mining is very common to do research ..so give me some positive response.

Yes, data mining is popular and it is good to work in a popular field. It means that you may eventually find a job in this field and that more people may read your research. It is much better to work on something popular than on something that is not.

thank you sir.. sir give me some current research topic in data mining.. i mean i read many paper but i am very confused to select some topic. give me some proper topic from current research.

It’s better that you choose a topic that you like. But if you really want some topics, I can give you some random topics: fuzzy sequential rules mining, incremental sequential rule mining etc.

Sir,,, i m in last year so i want to project on data mining so plz suggesst me sutaible topic in this area.

I want to do Phd. I cleared written exam for Phd and my interview schedule on 14th of July. In Interview,I have to represent my broad area of research interest.

After go through lots of Research Papers, I decide my broad area of research interest is Mining Web Log Files to improve the performance of website. Sir I want to use existing technique and make some modification in it and obtain better results.

But Sir, I am really confuse in how to justify my research methodology in interview. What should i say when they ask question like “what kind of techniques you want to use?” Because I have no Idea. Please Sir Help. Reply ASAP.

Congratulations for your interview. I think you need to read a few paper on weblog mining to find what are the main techniques. It is better if you can talk about a few techniques even if you just know the basic idea. For example, one technique that may be used is sequential pattern mining (discovering sequences frequently appearing in a set of sequences). It could be used to find what occurs often in the weblog to understand the behavior. Another technique is clustering if you want to find similar web users. Or if you want to predict what will be clicked next, you may use something like our CPT+ model: http://www.philippe-fournier-viger.com/PAKDD2015_sequence_prediction.pdf Those are just some example. There are many techniques that could be applied on weblog data. Actually choosing a technique depends on WHAT you want to do (what is your goal). Saying that your interest is “mining log files” does not mean much. What is your goal? Do you want to find patterns? Do you want to cluster the users? Do you want to predict what people will click on next? … etc. etc. I think that you need to define more clearly what is your goal. It may be more important than talking about the techniques.

Hello to everyone , sir I want to do mtech thesis in data mining . sir can u suggest some topics for thesis / project

Superb work sir really appreciating while reading .

Sir, now i am final year MCA..i can choose my project in Research area..But i cant no idea about that..But,still i have learned data mining i like to doing in my project also data mining technique in Clustering also..So,If i want to one Topic for my project..Pls,Say sir….

You can choose any recent paper published about clustering in a good conference and journal and improve their work.

Hello sir , I read all your suggestions about research topics i am an m.tech student i have studies grid clustering in minor thesis now i have to work on major thesis can u kindly suggest related topic plz plz plz i want to discuss it with you how can i discuss. i will be very thankfull.

Hi, I don’t work on grid clustering so I don’t know much about which topics are good related to grid clustering. Moreover, it takes times to find a topic. I cannot suggest topics.

Respected Prof.Phillippe,

I really appreciated your suggestion, you are guiding all of the needy people you did a great work sir. I also need your help in my research i will be very thankful. I have some topic in my mind but want to discuss for proceeding further.

Thank you so much for replying sir i just want suggestion about any open source tool of clustering which can perform grid clustering also, if you can help only any tool name i will work on it myself. i will be very thankful.

I don’t know about open-source tool for grid clustering.

But in my SPMF library, there are a few clustering algorithms : K-Means, DBScan, … Perhaps that some may be useful

thank you sir i have studied comparison of some algorithms ,what can i further do in clustering or few of its algorithms .Is there any other option in clustering for my research.

There is a lot of thing that one can do in clustering: make faster algorithm, make better clustering algorithm, apply clustering algorithm in new ways, combine clustering with some other techniques, etc. As I said in the blog post, to find a good topic, one need to read several papers, and then you may get some ideas about what other people have been doing recently.

Thank u for your tips to start our Phd. Sir can suggest some topics related to data mining in biological data .

In the blog post on top of this page, I explain how to find a topic. I cannot do it for you.

Ok sir thank you

Hello sir, I am studying M.sc 2yr,i have one research paper(project) for this sem sir…i don’t know that which area i select but i like to do in data mining..i know only little bit of knowledge in data mining sir…could u help me sir for which topic that iwill select in data mining..

The blog post on top of this page explains how to choose a topic.

Sir I want to start my thesis.. i want to work on data Mining specificly on clustering can u suggest me where to start or reach to find best problem?

Look at recent papers published in top data mining conferences and papers published in top data mining journals.

Sir, I am working in a telecom company for the last 10+ years and mainly in the IT wing. Now I wish to do a Phd in large data analysis for which I am having the required data. I am not having a correct idea regarding the way I have to proceed. Can you guide me in this regard. Thanking you

Your research supervisor should be able to help you.

HI. I want to do a M.Sc. in data mining security . But it is difficult to choose a topic. There are too many data mining topics. Is it a good idea?

Yes, it is a good area. Too many topics is good, it means that you can choose. You just need one topic.

hey Philippe,

i wanted to know whether it is necessary to have a good knowledge in statistics and maths to pursue research work in data mining? am interested in data mining but i don’t have good hold on stats and maths.. could you please suggest me?

Hi, It certainly helps. But it is not a requirement. You can choose a topic that is more algorithmic oriented for example and where there is less math and statistics. For example, if you work on designing algorithms for “clustering” or “pattern mining”, you can do something with not much math.

Thank you…that helped a lot

Hey Philippe, i wanted to know whether it is possible to combine classification and regression as hybrid model if i want to have to enhance classification prediction or regression models ,could you please suggest me some knowledge needed and tools .

Hey Philippe, i wanted to know whether it is possible to combine classification and regression as hybrid model if i want to enhance classification or regression prediction models ,could you please suggest me some knowledge needed and tools .

Hi, It is certainly possible. Actually, regression can be used to performed classification. For example, you may want to guess what is the salary of some employee and you have the salary of other employees from the same area. You may do some regression to get that information, and it could be seen as classification. This is just a simple example, but there are certainly more complex ways. Since I don’t do research on that topic, I cannot say too much about that. You would need to search a little bit and read recent papers to know more about what has been done recently.

I’m doing phd in big data mining. I wan to work on any real time scenario for research. Can you suggest me specific dataset/problem for it?

This is very broad. You could do for example stream mining to detect security attacks by analyzing network traffic. I think that there are such datasets available about network trafic. Besides, I think that whatever the topic that you choose, something important is to find some datasets whether from some companies, make your own datasets or download some public datasets.

hello sir, can u suggest any topic for research even other then data mining i needed it for my final year thesis…im really confused since last few days unable to find any topic..

If you don’t care about the topic, you can choose a data mining topic such as fuzzy sequential rule mining. This topic has probably not been done.

thnx a lot sir….. 🙂

I’m Selva from India,I’m interested in doing my Ph.D work in Natural Disaster Management using spatial data mining.Since the natural disaster management is a vast area I’m struggling to drill down into the exact area and also I’m worried about getting the proper data-sets on this area. Could you please suggest your ideas on this.

Thanks, Selva

Hi, I’m not familiar with this area. Maybe you should try to talk with some special about natural disaster. If there is some at your university, you may try to contact them and perhaps that they can provide some data. Also, maybe look at some government websites. Some places like Japan or Taiwan have many earquakes. I think you should be able to get data from these governement websites about the location and time of each earthquakes if you search carefully for example.

Thanks for the suggestion.

Regards, Selva

Dear Sir Thanks a lot for your such helps. A lot of students are facing these types of problems and you are helping in a very effective way. We are grateful to you. Could you tell me which are the latest research areas of data mining? In which conferences or journals I can find what people have been doing recently on data mining so that I can choose an area or topic on data mining for my PhD program?

I will be grateful if you help me in this regard.

Thanks………

Hi You are welcome. You may look at the data mining conferences : KDD, PAKDD, ICDM, PKDD, ICDE, CIKM, DAWAK, DASFAA, DEXA, ADMA, etc. also the data mining journals: TKDE, DMKD, TKDD, KAIS, etc.

There is a lot of possible topics. Some current trends are big data, social networks, etc. But you can also choose something else.

Thank you again sir…………

Sir..i want to do some work in data mining for my phd…sir my programming skill is weak .sir plz suggest me topic to research purpose which has less programming

If you are doing a PhD in computer science, you will certainly need to do some programming and need to improve your programming skills if they are not so good. Data mining in general requires to be good at programming especially if you want to design some algorithms, because you will want to make algorithms that are fast, since data mining algorithms are generally applied on large amount of data. If you are not good at programming, perhaps that you should choose a topic that invovle less programming such as research on e-learning, or you could still do data mining but more toward the applications of data mining rather than working on algorithms. For example, you could work on applying data mining to biomedical data, biology, e-learning etc. If you are good at math, another option is to take more of a math approach and use software such as Mathlab, etc.

Thanks a lot sir

Sir which language is used in data mining algorithm…can i learn this language at home?if i want to learn language for data mining ..which language i should learn..which book prefer to leraning that language…

Dear Sir I studied different papers from difference conferences and journals given by you. Thanks a lot for your suggestions. Actually I have very limited knowledge on data mining but I am interested too much to do my research in this area. I am ready to study a lot. But I have to prepare a PhD proposal within very short time. Now I guess I can work on “Spammer Detection Methods/mechanisms/techniques in social media systems or something related this”. But I can not be enough confident what should/might be the proper topic. Could you please help me in proper direction for choosing a topic in this regard.

Sir which language is used in data mining algorithm…can i learn this language at home?if i want to learn language for data mining ..which language i should learn..which book prefer to leraning that language…

I need PhD spicific topic in healthcare data mining, please

Hello sir, I am studying M.s.c and decision to do my research in data mining direction particular in revenue accounting fraud statement detection please sir i want to determine the algorithm that achieve my word correctly and display acceptance result thanks

Dear sir, I want to do some work for my phd in data mining especially sequential pattern mining on Big Data but i could not find any new specific problem in this area. would you please help me and suggest your idea to find a specific problem on this ?

Thanks you.

Hello, there are a lot of possibilities. You can combine any two topics to obtain a new topic. For example, I did not see any algorithms for sequential rule mining in big data. Designing a sequential rule mining algorithm running on big data framework such as Hadoop or Spark is a good topic. Besides, that there are many other possibilities. For example, you could combine : incremental mining + sequential pattern mining + big data, or any other combinations of topics.

Thanks a lot Sir.

It helps me a lot.

i interested in work on data mining . Also i have many years experience in fields of education. please introduce some topics about data mining in education. thank you.

You may read papers from the Educational Data Mining conference (EDM), or related conferences such as Artificial Intelligence in Education (AIED), Intelligent Tutoring Systems (ITS), and others to see what are the current problem related to data mining and education.

Sir, I want to do research in Parallelisation of Data Mining Algorithms. I am also good in Optimization techniques like Genetic algorithms. Please suggest me topic related to this. Thanks in advance…

I suggest to read recent papers in data mining conferences/journals to find a good topic. It takes time to find a good topic.

Actually I want to work on Distributed framework or shared frame work of Data mining algorithms like clustering and classification algorithms either on Hadoop Mapreduce or using OpenMP/MPI, but which application I choose to apply data mining clustering or classification algorithm, I am little bit confused. I do not want to go towards Semantic web mining … Please suggest…..

Data mining can be applied in almost any domains: bioinformatics, medecine, psychology, education, etc. In my opinion, you should choose a domain (1) that you like, and (2) where you can easily collect data to be used by your data mining algorithms.

Sir , I want to work on agricultural data.please suggest current topic. am are work “study of agricultural land soil using classification techniques” in M.Phil. program. I am look a P.Hd Topic in data mining .

You need to find a topic by yourself. I cannot help you.

Sir, I want to do P.hd in data mining.Please suggest me title for my work

Algorithms for sequential rule mining in data streams

Hi Sir , would you please suggest me a problem in high utility sequential pattern mining ?

Thanks alot

You can combine high utility seq. pattern mining with any other topic such as fuzzy pattern mining, incremental pattern mining, stream mining, etc. You may read other papers and try to combine two ideas to get a problem.

would you please suggest me a topics for thesis in information technology major in business analytics.

thanks a lot.

I don’t really have time to find topics for other people than my own students. Sorry. You should read papers in recent conferences and journals and choose a topic that you like and try do to better or do something that other people did not do.

Hello sir, I have bit knowledge in Data Mining techniques. If i apply DM techniqes and do some analysis on any real time problem, does it consider for PhD. because i am not doing anything new,just applying DM techniques and getting some reslut. Please help me in this regard

It can be. The goal of a Ph.D. is to contribute to the advancement of knowledge in some field. You may either work on more fundamental problems or working on some more applied problems. For example, one may design a new data mining algorithm (a more fundamental problem), but one may also use existing data mining techniques do something new or better in some fields (for example, use existing algorithms in a new way to identify the authors of texts, or to discover communities in social networks). What is important is that a PhD need bring something novel. So if you work on an applied problem, you still need to bring some novelty but at the application level. Personally, I prefer topics at a fundamental level (design of algorithms) but there many people who work on a more applied level (for example, you may check any conference on e-learning, there is a lot of applied research).

Hi how are you?i hope u are doing well actually im really interested in data mining topics such as clustring ,data mining in big data ive read many articles but the problem is i could’t find something interesting what sub-topics in “data mining in big dat”a that can i work on ?

could you help me with

I cannot find a topic for you. You may ask help from your supervisor. He should be able to help you. Otherwise, you may look at recen data mining conferences to look for some topics. “data mining” and “big data” is very broad. It can mean basically anything in data mining.

im afraid that i would spend more time looking for topic,and after that ill find that the topic is already solved.

i wan work on something likes this in general :processing big data and finding the relations and interesting pattern is difficult ,So ,what kind of challenges theta we maybe face when processing big date and how can we provide efficient data mining techniques to overcomes the issues? would be a good PhD topic? or i have to look to something different? thank in advance.

Before doing any research project, one should read enough papers about the topic to know what already exist, and make sure that the problem has not been solved. If you want to become a researcher, this is something that you need to learn to do. Even if it takes a lot of time, you still need to do it, and it is important that you do it.

Ok, so you want to find patterns or relationships in big data… But that is still not a topic because it is too general. Finding patterns in big data could mean almost any data mining algorithms applied to big data. So you still did not define a topic. To define a topic, you would need to 1) define what kind of patterns you want to find: Clusters, outliers, frequent patterns, subgraphs, communities, etc., 2) and define in what kind of data: graphs, transaction databases, multimedia data, spatial data, data streams, etc. and 3) perhaps also what kind of approach you want to use to find these patterns.

So I cannot say whether it is a good topic because your topic is still too general. Finding a good topic takes time. There are an infinite amount of “good topics” that one could find. But as I said before, I cannot do the litterature review for you. You need to do it by yourself and evaluate by yourself if it is a good topic. Even in data mining, I’m not familiar with all the topics, and I will not read the papers for you to tell you if it is a good topic or not, unless your ask me about something that is directly related to what i’m doing.

that’s really helpful .thank you very much.

Please suggest me application of confabulation association rule mining for multidimensional association rule generation.

I did not read about “confabulation association rules” so I cannot say much about it. You may ask the authors of that paper.

hi Philippe when i am reading your answer to the comments , now i am sure about the topic must be specific and not general .

what i want is i need to do classification on cloud data can you help in this way

preparing a paper of applying classification techniques on cloud data

thanks a lot

Good that you know more about how to look for a topic. But I cannot help further than that. I am very busy and I need to take care of my own research.

i am very much interest to purse my PhD degree in Data Mining field. i need your guild lines to select my PhD topic in opinion mining and sentiment analysis. please share some recent research areas in this field.

I am very interested to pursue research in Data Mining in Healthcare Science Applications, Please suggest me some recent popular topics where I can explore to start my research.

i dont work on this topic. You may look at recent research papers.

Hello Sir, I am a computer science student, entering into research for the first time. I have been searching for topics in data mining. I wanted to ask what are the topics related to stocks that I can research on or write a thesis on. There is a lot of research going in this field. I m really confused on which direction to go- something less explored and with a lot of scope of research. It will be great if you could suggest an approach on this topic.

P.S. If you have any suggestion on a ‘popular topic’ -as you suggested, that would make my way easier to some conferences, would be of great help.

It would be hard to suggest topics about stocks since I don’t work on that. But some typical problems that have previously seen are to predict the stock market, detect fraud on the stock market, find correlations or patterns indicating that some stocks are related and behave the same way on the stock market…. I think you could find more ideas by searching a little bit on Google Scholar

Best regards

Thanks for your helpful suggestion.

Do you know anybody who is currently working on this topic who i can ask questions from? I wish to get more insight on this.

No. I don’t personally know anybody working on that. But if you find some papers about stock markets on Google Scholar, you can always send e-mail to the authors to ask them questions or ask for their dataset. Sometimes they will give you some advice or maybe even their datasets.

Thank You once again 🙂

Hi Philippe, Iiam looking forward my PhD in DataMining. Iam interested in Social Newtwork Mining. How and where can we apply datamining algorithms ( clustering, classification algorithms, etc.) on Social Network Analysis. And also how can we apply Neural Networks on datamining applications.

Best regards.

Hi, Wish you good luck for you Ph.D. This is some very broad questions. For applications of data mining on social networks, you could have a look at the papers published at the ASONAM conference ( international conference on Advances in Social Network Analysis and Mining ) which is about data mining and social networks. You will see that there are many topics. It would be too long to list all of them here. You could also check journals related to that topic and papers on Google Scholar.

Neural networks also have hundreds of applications. Basically, you could see neural networks as a data mining technique. So the applications of neural networks in data mining, would be all the applications of neural networks, and there are a lot.

Thanks alot Philippe for your valuable suggestion.

i want good thesis topic in data mining for ph.d

then you may read the blog post on that page which explain how to find a topic

sir am doing m.phil, my guide suggest to learn scikit website. pls suggest some topic regarding this.

Scikit is just a tool that you may use in your research. It can be helpful. But you should perhaps find a topic first instead of looking at scikit to find a topic. That is my opinion

Thank you sir.I decided to do in medical field. Is it correct decision ? and now is it current trend? I am just confused sir. Please suggest me some of the field which are in current trend.

I don’t work in the medical field. I work in the field of data mining. The medical field is a possible application of data mining. If you can get some real medical data and know some people in the medical field that can guide you in your project, then why not choosing that field. I guess it could be ok. But even if you choose a field, you still need to find a specific topic. The “medical field” is still very broad and could lead to an infinite amount of topics. I suggest to read papers in recent conferences and journals related to your interest to see what people are working on.

Ok sir. Data mining is my domain sir, in that i decided to do healthcare or big data application. Please tell me which is sufficient to collect data. Also please suggest me some of the other application which are more effective.

“big data application” or “healthcare” is still very broad. You need to read some recent papers and see what other researchers are doing to find a good topic. I cannot do that for you. It can take actually quite a lot of time to find a good topic. But you can always ask your supervisor to help you about that.

sir , this blog is really useful. I am planning to do datamining in the feild of nano technology . any ideas or suggestions of topics related to this .plz suggest.

Glad you like the blog.

I don’t work on nanotechnology.

Hi. Right now I’m planning on continue my research study on malware analysis. I’m thinking of using data mining approach in my research. However, since i’m doing in PhD level, my supervisor do not want me just applying the data mining technique. He always asked me about the weakness/limitations I’ve found in data mining. However, as far as i’m concern, there is none limitations on data mining. So, may I asked if you or any visitors in this blog have any idea about the data mining weaknesses/limitations in malware analysis that I have overlooked?

Thanks again.

I understand what you mean. At first, it may seems that a technique has no limitations. But there is always some. What you could do is to choose a technique from the literature, try it, and after you tried it, you will certainly think about some way to improve it. For example, if you try some classification technique to classify malwares, then what about considering also the time dimension? what about doing real-time classification? what about developing an approach where your algorithm can say how many percent certain he is that a program is a malware? etc. There is generally always some way to extend a technique for example by considering more information such as time etc. Besides, another possibility is to combine characteristics from different approaches that you like. By reading a few papers, you may try to see the different approach for classifying malwares and then try to combine the best characteristics of all these approaches. This is just some ideas.

Thanks for your quick reply. But I have questions about combining a characteristic from different approaches like you said. I had confused with the meaning of characteristic? is it characteristic of the malware or the technique in classification it use (eg c4.5, dt etc) ? and by mention different approaches, did you mean by combining statistic and machine learning? I’m so sorry for asking but I’m really stress right now. I’m glad you’re replying me.

I mean, it could be different characteristics of the data mining approach. For example, maybe there is an algorithm A for classification, and another algorithm B for classification that consider time, and another algorithm C for classification that let you add constraints when doing the classification. If you think that your approach need classification + time + constraint, you could try to combine the algorithms A + B + C in a single new algorithm. This is just some general ideas. In general, the more information you consider such as time, the more complicate the problem become, and then you need to extend the original algorithms to consider this additional information. I just tell you this as some general idea. You could see how that could apply to your problem by reading some papers and comparing the different data mining approaches to then try to take the best of each approach if possible. Or try to add something new that other people did not do.

Thank you so much for replying. I’m feeling great I have stumble upon your website today. Thanks again. Your website is awesome. May God bless you & your family.

You are welcome. Good luck. By the way, you may also check my data mining forum:

http://forum.ai-directory.com/list.php?5

It is a place for discussing data mining.

Dear sir, presently i am teaching the pg and ug students for the c omputer science , and i had choosen to work for my PH.D. from different university privately. This is an request kindly suggest the topics which is convenient in teaching and working both related to my ph.d. work.

Finding a topic takes time, so I will not do that for you. You can read the blog post at the top of this page which explains how to search for a topic.

I like your collection, thanks for sharing this wonderful collection of themes with us.i am working in Cloud Erp Software Companies In Chennai

Hi Sir, I Rasheeduddin registered Ph.D In Data Mining Clustering My Title is

“Improving level of efficiency through K Means Algorithm in Social Networking Data Base”.

Actually i want to implement the K Means Algorithm in Social Networking Data Base.

Please Suggest me any changes required to this Title and what type of Back Ground work is required to start. please guide me/ suggest me

Sir, I have Qualified in OU Ph.D Entrance test. I want to do Ph.D on data mining. so please tell me the topic of research on data mining or any other area.

Thank you sir

Could you please suggest me where I can get more information and where I can get the recent works on opinion mining?

Hi, I would recommend to use Google Scholar to search for papers. There is a features that let you search by year. You can search for papers from 2012- 2016 for example using Google Scholar. Otherwise, you may also check the journals and conference on data mining or similar research areas. But, Google Scholar is a very good place for searching for articles.

Thanks……..Thanks a lot you again.

Can you please tell me also some journals and conferences on pattern recognition???

I don’t work on pattern recognition so I cannot say too much about that. But you may check some pages like this one which provides some kind of rankings of conferences/journals:

http://www.scimagojr.com/journalrank.php?category=1707

Thanks again. Really I am grateful to you…………

my area of interest is bank data mining can you please suggest some topic on it ?

I don’t work on bank data, so it is hard for me to suggest something. But a typical topic for bank data is to evaluate the credit record of customer to detect whether they will pay back their debt or not for example. There exists some papers on that already. You may find using Google Scholar.

hi could you suggest some topic for ” Data mining for customer relationship management” please

Sir, I have Qualified in Ph.D Entrance test. I want to do Ph.D on data mining. I am interested to do phd in revenue management/system by using data mining technique . can u guide me this interest is good or bad for the project work

The blog post above gives you some guidance. Have you read it?

I want to do Mtech Research in data mining. please suggest me a topic in data mining which is somehow related to networking.

I suggest to read the blog post on top of this page that explains how to find a topic. 🙂

need opinion, target of my topic is “user identification over social network”. i just want to apply changes through these techniques “clustering and outliers”. sir kindly tell what is the scope of topic? if its fine then please generate impressive topic name for me.

I don’t know what you want me to tell you about the “scope of this topic”.

But if you choose this topic, the topic name could be “Novel clustering and outlier detection approaches to user identification in social networks”.

Thanx , Philippe Founier-Viger

SIR what are the current problems in identification of user in social networks, which problems should i target?

I want to get example title for my thesis in computer science.I am interested in data mining.Please sir.

If you want some example of titles, you may look at Google Scholar. There are a lot of examples. Or you may look at data mining journals and conferences. There are a lot of examples.

Which method I can used for passport data analysis? Please guided me the latest or pooular method for that.

I never worked on passport analysis. It depends what you want to do. Analyzing a passport to do what? If you want to analyze the picture, then you could use some image processing techniques. But it really depends what you want todo. The best would be that you search what other people have been doing on this topic recently in Google Scholar for example. As I said, I don’t work on this topic, so i cannot tell you the method that people have been using.

Hello sir I want to discover the travel pattern from passport data analysis.

I want to discover the travel pattern from passport data analysis.So which method I can used sir?

Many methods could be applied: – Find people with similar travel patterns –> some clustering – Find people with abnormal travel patterns –> outlier detection – Find some frequent travel patterns –> pattern mining – Classify the travellers based on their travel patterns –> classification

This is just some basic idea. Those area some of the most popular areas in data mining. Depending on how your data looks like etc, you may choose different techniques.

Yes thank you sir.

Please, guidence for the new method(update method) for this.My reference paper used like k-means, apriori algorithm but this methods are olds.So my supervisor told me to used new method.I want to apply the update method for this topics.

To apply some new method, you first need to know what the researchers have already done before you. So as I said previously, what you need to do is to read some research papers about discovering travel patterns. Then, you can understand what other people have done and do something new or something different. There is no way to avoid that step. If you ask me to recommend you something new, I cannot really tell you because I did not read the papers on discovering travel patterns, and I don’t know what people have done already. This, you need to do it by yourself.

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Dear professor, i have interest association rule mining (frequent, periodic, utility, and closed patterns mining). could you suggest me the mathematical and statistical portion for study to design new algorithm on the base of exiting algorithm like (Apriori, Eclat, and fp-Growth).

i will be thankful for this help,

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Trending Data Mining Thesis Topics

            Data mining seems to be the act of analyzing large amounts of data in order to uncover business insights that can assist firms in fixing issues, reducing risks, and embracing new possibilities . This article provides a complete picture on data mining thesis topics where you can get all information regarding data mining research

How does data mining work?

• A standard data mining design begins with the appropriate business statement in the questionnaire, the appropriate data is collected to tackle it, and the data is prepared for the examination.
• What happens in the earlier stages determines how successful the later versions are.
• Data miners should assure the data quality they utilize as input for research because bad data quality results in poor outcomes.
• Establishing a detailed understanding of the design factors, such as the present business scenario, the project’s main business goal, and the performance objectives.
• Identifying the data required to address the problem as well as collecting this from all sorts of sources.
• Addressing any errors and bugs, like incomplete or duplicate data, and processing the data in a suitable format to solve the research questions.
• Algorithms are used to find patterns from data.
• Identifying if or how another model’s output will contribute to the achievement of a business objective.
• In order to acquire the optimum outcome, an iterative process is frequently used to identify the best method.
• Getting the project’s findings suitable for making decisions in real-time

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Data Mining Tasks 

• Data mining finds application in many ways including description, Analysis, summarization of data, and clarifying the conceptual understanding by data description
• And also prediction, classification, dependency analysis, segmentation, and case-based reasoning are some of the important data mining tasks
• Regression – numerical data prediction (stock prices, temperatures, and total sales)
• Data warehousing – business decision making and large-scale data mining
• Classification – accurate prediction of target classes and their categorization
• Association rule learning – market-based analytical tools that were involved in establishing variable data set relationship
• Machine learning – statistical probability-based decision making method without complicated programming
• Data analytics – digital data evaluation for business purposes
• Clustering – dataset partitioning into clusters and subclasses for analyzing natural data structure and format
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• Data preparation and cleansing – conversion of raw data into a processed form for identification and removal of errors

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 The following are the important stages or phases in developing data mining thesis topics.

• First of all, you need to identify the present demand and address the question
• The next step is defining or specifying the problem
• Collection of data is the third step
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Usually, our experts help in writing codes and implementing them successfully without hassles . By consistently following the above steps you can develop one of the best data mining thesis topics of recent days. Furthermore, technically it is important for you to have a better idea of all the tasks and techniques involved in data mining about which we have discussed below

• Data visualization
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If you are looking forward to selecting the best tool for your data mining project then evaluating its consistency and efficiency stands first. For this, you need to gain enough technical data from real-time executed projects for which you can directly contact us. Since we have delivered an ample number of data mining thesis topics successfully we can help you in finding better solutions to all your research issues. What are the points to be remembered about the data mining strategy?

• Furthermore, data mining strategies must be picked before instruments in order to prevent using strategies that do not align with the article’s true purposes.
• The typical data mining strategy has always been to evaluate a variety of methodologies in order to select one which best fits the situation.
• As previously said, there are some principles that may be used to choose effective strategies for data mining projects.
• Since they are easy to handle and comprehend
• They could indeed collaborate with definitional and parametric data
• Tare unaffected by critical values, they could perhaps function with incomplete information
• They could also expose various interrelationships and an absence of linear combinations
• They could indeed handle noise in records
• They can process huge amounts of data.
• Decision trees, on the other hand, have significant drawbacks.
• Many rules are frequently necessary for dependent variables or numerous regressions, and tiny changes in the data can result in very different tree architectures.

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Current methods in Data Mining

• Prediction of data (time series data mining)
• Discriminant and cluster analysis
• Logistic regression and segmentation

Our technical specialists and technicians usually give adequate accurate data, a thorough and detailed explanation, and technical notes for all of these processes and algorithms. As a result, you can get all of your questions answered in one spot. Our technical team is also well-versed in current trends, allowing us to provide realistic explanations for all new developments. We will now talk about the latest data mining trends

Latest Trending Data Mining Thesis Topics

• Visual data mining and data mining software engineering
• Interaction and scalability in data mining
• Exploring applications of data mining
• Biological and visual data mining
• Cloud computing and big data integration
• Data security and protecting privacy in data mining
• Novel methodologies in complex data mining
• Data mining in multiple databases and rationalities
• Query language standardization in data mining
• Integration of MapReduce, Amazon EC2, S3, Apache Spark, and Hadoop into data mining

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Future Research Directions of Data Mining

• The potential of data mining and data science seems promising, as the volume of data continues to grow.
• It is expected that the total amount of data in our digital cosmos will have grown from 4.4 zettabytes to 44 zettabytes.
• We’ll also generate 1.7 gigabytes of new data for every human being on this planet each second.
• Mining algorithms have completely transformed as technology has advanced, and thus have tools for obtaining useful insights from data.
• Only corporations like NASA could utilize their powerful computers to examine data once upon a time because the cost of producing and processing data was simply too high.
• Organizations are now using cloud-based data warehouses to accomplish any kinds of great activities with machine learning, artificial intelligence, and deep learning.

The Internet of Things as well as wearable electronics, for instance, has transformed devices to be connected into data-generating engines which provide limitless perspectives into people and organizations if firms can gather, store, and analyze the data quickly enough. What are the aspects to be remembered for choosing the best  data mining thesis topics?

• An excellent thesis topic is a broad concept that has to be developed, verified, or refuted.
• Your thesis topic must capture your curiosity, as well as the involvement of both the supervisor and the academicians.
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Research Topics in Data Mining

• Handling cost-effective, unbalanced non-static data
• Issues related to data mining and their solutions
• Network settings in data mining and ensuring privacy, security, and integrity of data
• Environmental and biological issues in data mining
• Complex data mining and sequential data mining (time series data)
• Data mining at higher dimensions
• Multi-agent data mining and distributed data mining
• High-speed data mining
• Development of unified data mining theory

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30 Data Mining Projects [with source code]

Machine learning (ml) data mining.

Open-Source Internship opportunity by OpenGenus for programmers. Apply now.

Introduction

Data mining has become an increasingly important field in recent years as the amount of available data has exploded. With the rise of big data, businesses and organizations have found themselves with a wealth of information that they can use to gain insights into their operations, customers, and markets. Data mining projects are a key way to harness the power of this data and turn it into actionable insights.

In this article at OpenGenus, we will explore some of the most interesting and innovative data mining project ideas that have been undertaken in recent years. These projects demonstrate the power of data mining to uncover insights and drive real-world outcomes. From predicting disease outbreaks to identifying fraudulent behavior, data mining has the potential to transform the way we do business and solve some of the world's most pressing problems.

These projects are a strong addition to the portfolio of Machine Learning Engineer.

List of Data Mining projects:

Fraud detection in credit card transactions

Predicting customer churn in telecommunications, predicting stock prices using financial news articles, predicting customer lifetime value in retail, banking credit defaulter identification, personalized product recommendations in e-commerce, detecting fictitious insurance claims, social media post sentiment analysis, traffic prediction using sensor data, predicting customer preferences in hospitality, predicting diabetes risk using patient data, estimating customer lifetime value, email classification, movie prediction, customer segmentation in retail, predicting house prices, healthcare fraud detection, recommending movies to users, predicting student performance, finding creditworthy borrowers, forecasting flight delays, healthcare insurance claim fraud detection, recommending products to users based on their browsing history, predicting customer churn in subscription services, identification of potentially fraudulent transactions in banking, predicting employee attrition, recommending products to users, detecting cyberattacks, forecasting weather patterns, identifying fake news.

Let's see each one of them one by one :

The objective of fraud detection in credit card transactions is to separate out fraudulent from legitimate transactions. By examining transaction patterns and metadata, as well as supervised learning algorithms like logistic regression or random forests, this can be accomplished.

• Project title: Fraud detection in credit card transactions
• Dataset used: European credit card holders consisting of rows of transactions made by credit cards. The total number of transactions captured were 500,000 and the number of features captured were 320.
• Difficulty level: 4
• Concepts involved: Data Cleaning, Memory Reduction, Under Sampling, Dimensionality Reduction, Feature Selection, Outlier detection
• Source code: https://github.com/mathiasjess/Credit_Card_Fraud.git

The goal of telecom customer churn forecasting is to identify which customers are most likely to leave a telecom company and why. Data on usage patterns, demographics, and customer support interactions can be used to achieve this, along with machine learning tools like decision trees and neural networks.

• Project title: Predicting customer churn in telecommunications
• Dataset used: List of people leaving a organization
• Difficulty level: 3
• Concepts involved: Data Cleaning, Under Sampling, Dimensionality Reduction, Feature Selection, Outlier detection, Decision tree
• Source code: https://github.com/Nikitasinha17/Telco-Customer-Churn-Prediction-.git

Using financial news articles to forecast stock prices: The objective is to create a model that can assess news articles and forecast their effects on stock prices. This can be done by applying time series forecasting techniques like ARIMA or LSTM and using natural language processing (NLP) techniques to extract pertinent information from news articles.

• Project title: Predicting stock prices using financial news articles
• Dataset used: contain the twitter feed from companies
• Concepts involved: Data Cleaning, Sampling, Dimensionality Reduction, Feature Selection, Outlier detection, Decision tree, Sentiment Analyzer
• Source code: https://github.com/TapasSenapati/StockPrediction.git

Estimating the anticipated revenue that a customer will generate over the course of their relationship with a retail company is the goal of customer lifetime value prediction in retail. RFM (recency, frequency, monetary) analysis, demographic data, and historical transaction data can all be used for this.

• Project title: Predicting customer lifetime value in retail
• Dataset used: contain data of customers from different companies
• Concepts involved: Data Cleaning, Down Sampling, Dimensionality Reduction, Feature Selection, Outlier detection, Decision tree, Sentiment Analyzer, Noise removing
• Source code: https://github.com/mukulsinghal001/customer-lifetime-prediction-using-python.git

The objective is to identify which clients are likely to default on their loans. This can be achieved by applying machine learning techniques like logistic regression or decision trees, as well as data on previous loan applications and repayment histories, as well as socioeconomic and demographic factors.

• Project title: Banking credit defaulter identification
• Dataset used: data of credit card clients
• Difficulty level: 5
• Source code: https://github.com/MaxineTan/DataMiningProject.git

The goal of personalized product recommendations in e-commerce is to give customers recommendations based on their browsing and purchasing patterns. By examining product descriptions and reviews, collaborative filtering algorithms and NLP techniques can accomplish this.

• Project title: Personalized product recommendations in e-commerce
• Difficulty level: 2
• Concepts involved: Pre-processing, data clean up, noise remove
• Source code: https://github.com/alanramponi/recommEngine.git

The objective is to spot fictitious or suspicious insurance claims. This can be accomplished by examining patterns in historical fraud cases and claims data, as well as by using supervised learning algorithms.

• Project title: Detecting fictitious insurance claims
• Dataset used: data of insurance claiming clients
• Concepts involved: Pre-processing, data clean up, noise remove, analyzing data
• Source code: https://github.com/rakiiibul/auto_insurance_fraud.git

The goal is to examine posts on social media and categorize them according to sentiment (positive, negative, or neutral). NLP methods like sentiment analysis and machine learning algorithms like SVM or Naive Bayes can be used for this.

• Project title: Social media post sentiment analysis
• Dataset used: data of social media comments-Twitter
• Concepts involved: Preprocessing and Cleaning, data clean up, noise remove, analyzing data, Story Generation and Visualization from Tweets
• Source code: https://github.com/sharmaroshan/Twitter-Sentiment-Analysis.git

The objective of traffic prediction using sensor data is to foresee traffic patterns and levels of congestion on roads and highways. Using sensor data from GPS devices and traffic cameras, as well as machine learning techniques like time series forecasting or clustering, this can be accomplished.

• Project title: Traffic prediction using sensor data
• Dataset used: data of traffic sensor records
• Concepts involved: data clean up, noise remove, analyzing data, outliers detection
• Source code: https://github.com/bdice/advanced-data-mining-project.git

The goal of customer preference forecasting in the hospitality industry is to identify the features and services that guests are most likely to seek out in a hotel or resort. Demographic information, historical reservation and review information, and machine learning methods like clustering or decision trees can all be used for this.

• Project title: Predicting customer preferences in hospitality
• Dataset used: customer likeness data
• Concepts involved: preprocessing, duplicate data clean up, noise remove, analyzing data
• Source code: https://github.com/PraveenKumarGarlapati/TextMining_Hospitality.git

The objective is to identify patients who are at risk of developing diabetes in the future. Diabetes risk prediction using patient data. Using patient information like BMI, blood sugar levels, and family history, as well as machine learning techniques like logistic regression or decision trees, this can be accomplished.

• Project title: Predicting diabetes risk using patient data
• Dataset used: patient data
• Concepts involved: preprocessing, noise remove, analyzing data
• Source code: https://github.com/jerisalan/Diabetes-Prediction.git

The objective is to forecast the anticipated revenue that a client will produce over the course of their relationship with an insurance provider. RFM analysis, demographic data, and historical claim data can all be used for this.

• Project title: Estimating customer lifetime value
• Dataset used: Customer lifetime evaluation data
• Source code: https://github.com/sanjay-rendu/data_mining_project.git

The objective is to categorize emails as spam or not. NLP methods like text classification and machine learning algorithms like SVM or Naive Bayes can be used for this.

• Project title: Email classification
• Dataset used: all received email data
• Concepts involved: Data Cleaning, Down Sampling, Dimensionality Reduction, Feature Selection, Outlier detection
• Source code: https://github.com/iamdooboy/Data-Mining.git

Predicting which movies are likely to become hit and which are to be flop using ratings. Utilizing data on usage trends, demographics, and people interactions, as well as machine learning techniques like decision trees or neural networks, this can be accomplished.

• Project title: Movie prediction
• Dataset used: Other movies data(ratings and box office)
• Source code: https://github.com/iaperez/DataMiningProject-Movie.git
• Project title: Customer segmentation in retail
• Dataset used: Customer purchase history
• Source code: https://github.com/mathchi/Customer-Segmentation-with-RFM-Analysis.git

The objective is to create a model that can forecast a home's selling price based on attributes like size, location, and amenities. Regression methods like linear regression and decision trees can be used to accomplish this.

• Project title: Predicting house prices
• Dataset used: Data about area and amenities
• Concepts involved: Preprocessing, Feature Selection, Outlier detection, decision tree
• Source code: https://github.com/gilangsamudra/Data_Mining_HousePrices.git

The objective is to spot potentially fraudulent healthcare claims. This can be accomplished by examining patterns in historical fraud cases and claims data, as well as by using supervised learning algorithms.

• Project title: Healthcare fraud detection
• Dataset used: User's history of browsing, review history
• Concepts involved: Preprocessing, Under Sampling, Dimensionality Reduction, Feature Selection, Outlier detection, decision tree, anomaly detection
• Source code: https://github.com/Rainie-Hu/Fraud-Detection.git

Providing users with personalized movie recommendations based on their viewing preferences and ratings is the goal of this feature. By examining movie descriptions and reviews, collaborative filtering algorithms and NLP techniques can accomplish this.

• Project title: Recommending movies to users
• Concepts involved: Preprocessing, Under Sampling, Dimensionality Reduction, Feature Selection, Outlier detection
• Source code: https://github.com/spChalk/Movie-Recommendation-System.git

The objective is to forecast a student's academic performance using their demographic information and prior grades. Machine learning methods like decision trees and regression can be used for this.

• Project title: Predicting student performance
• Dataset used: Performance data of students
• Source code: https://github.com/ashishT1712/Data-Mining-Student-Performance.git

The objective is to identify the loan applicants who have the highest likelihood of repaying their loans. This can be accomplished by examining historical loan application and repayment data as well as supervised learning algorithms like logistic regression or random forests.

• Project title: Finding creditworthy borrowers
• Dataset used: Data of customer's transactions & past data
• Concepts involved: Preprocessing,data cleaning, Under Sampling, Dimensionality Reduction, Feature Selection, Outlier detection, decision tree
• Source code: https://github.com/Amitabh23/Credit-Scoring-using-Machine-Learning-Techniques.git

Based on past experience and outside variables like weather, the aim is to forecast the likelihood that a flight will be delayed. Machine learning methods like decision trees or neural networks can be used to accomplish this.

• Project title: Forecasting flight delays
• Dataset used: Flight data (Arrival & departure)
• Concepts involved: Data Cleaning, Under Sampling, Dimensionality Reduction, Feature Selection, Outlier detection
• Source code: https://github.com/Fukeng/Flight-delay-forecast.git

The goal is to spot erroneous or suspicious healthcare insurance claims. This can be accomplished by examining patterns in historical fraud cases and claims data, as well as by using supervised learning algorithms.

• Project title: Healthcare insurance claim fraud detection
• Dataset used: Healthcare insurance data of customers
• Concepts involved: Preprocessing, analyzing data, noise detection, removing duplicates, data cleaning

Users will receive personalized product recommendations based on their browsing history and preferences. Recommending products to users based on their browsing history. By examining product descriptions and reviews, collaborative filtering algorithms and NLP techniques can accomplish this.

• Project title: Recommending products to users based on their browsing history
• Dataset used: browser history data of customers
• Concepts involved: Preprocessing, analyzing data, removing duplicates
• Source code: https://github.com/zhtea/chrome_mining.git

Identifying subscribers who are likely to churn (cancel their subscription) is the goal of customer churn prediction in subscription services. Using data on usage patterns, demographics, and customer support interactions, as well as machine learning methods like decision trees or neural networks, this can be accomplished.

• Project title: Predicting customer churn in subscription services
• Dataset used: Customer usage pattern data
• Concepts involved: Data Cleaning, Under Sampling, Dimensionality Reduction, Feature Selection, Outlier detection, decision tree, anomaly detection, filtering
• Source code: https://github.com/jason-learn/Churn-Prediction-Challenge.git

The objective is to locate transactions. This can be done by examining transaction patterns and metadata, as well as supervised learning algorithms.

• Project title: Identification of potentially fraudulent transactions in banking
• Dataset used: Bank transactions
• Concepts involved: Data Cleaning, Under Sampling, Dimensionality Reduction, Feature Selection, Outlier detection, decision tree, anomaly detection, NLP, filtering, examine patterns
• Source code: https://github.com/jackyhuynh/Realtime_Fraud_Transaction_Detection.git

Based on their performance, tenure, and other factors, the goal is to identify the employees who are most likely to leave a company. Machine learning methods like logistic regression and decision trees can be used to accomplish this.

• Project title: Predicting employee attrition
• Dataset used: Employee data
• Concepts involved: Data Cleaning, Dimensionality Reduction, Feature Selection, Outlier detection
• Source code: https://github.com/SharonLiXX/Data-mining.git

Users will receive personalized product recommendations based on their social media activity and preferences. Recommending products to users based on their social media activity. Collaborative filtering algorithms and NLP techniques for social media post analysis can be used to accomplish this.

• Project title: Recommending products to users
• Dataset used: List of social media activity of users
• Concepts involved: Data Cleaning, Under Sampling, Dimensionality Reduction, Feature Selection, Outlier detection, decision tree, anomaly detection, NLP, filtering

By examining network activity and patterns, it is possible to identify cyberattacks in real time. Machine learning methods like clustering and anomaly detection can be used to accomplish this.

• Project title: Detecting cyberattacks
• Dataset used: List of network activities in certain time period
• Concepts involved: Data Cleaning, Under Sampling, Dimensionality Reduction, Feature Selection, Outlier detection, decision tree, anomaly detection
• Source code: https://github.com/scusec/Data-Mining-for-Cybersecurity.git

Predicting weather patterns like temperature, precipitation, and wind speed is the objective. Regression and time series forecasting are two examples of machine learning techniques that can be used to accomplish this.

• Project title: Forecasting weather patterns
• Dataset used: Weather of different area
• Source code: https://github.com/lawrensiya/Project-Tenki.git

The aim is to detect fake news articles by analyzing their content and metadata. This can be achieved using NLP techniques such as sentiment analysis and machine learning algorithms such as SVM or Naive Bayes.

• Project title: Identifying fake news
• Dataset used: List of news
• Source code: https://github.com/pmacinec/fake-news-datasets.gitw

With this article at OpenGenus, you must have a strong idea of Data Mining project ideas.

82 Data Mining Essay Topic Ideas & Examples

🏆 best data mining topic ideas & essay examples, 💡 good essay topics on data mining, ✅ most interesting data mining topics to write about.

• Data Mining Classifiers: The Advantages and Disadvantages One of the major disadvantages of this algorithm is the fact that it has to generate distance measures for all the recorded attributes.
• Data Mining Role in Companies The increasing adoption of data mining in various sectors illustrates the potential of the technology regarding the analysis of data by entities that seek information crucial to their operations.
• Data Mining in Social Networks: Linkedin.com One of the ways to achieve the aim is to understand how users view data mining of their data on LinkedIn.
• Disadvantages of Using Web 2.0 for Data Mining Applications This data can be confusing to the readers and may not be reliable. Lastly, with the use of Web 2.
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IvyPanda. (2024, March 2). 82 Data Mining Essay Topic Ideas & Examples. https://ivypanda.com/essays/topic/data-mining-essay-topics/

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Home > Statler College of Engineering and Mineral Resources > MININGENG > Mining Engineering Graduate Theses and Dissertations

Mining Engineering Graduate Theses and Dissertations

Theses/dissertations from 2024 2024.

CHARACTERIZATION AND EVALUATION OF VARIOUS BIOCHAR TYPES AS GREEN ADSORBENTS FOR RARE EARTH ELEMENT RECOVERY FROM AQUEOUS SOLUTIONS , Oluwaseun Victor Famobuwa

Selective Recovery of Various Critical Metals from Acid Mine Drainage Sludge , Gorkem Gecimli

Theses/Dissertations from 2023 2023

Development of A Hydrometallurgical Process for the Extraction of Cobalt, Manganese, and Nickel from Acid Mine Drainage Treatment Byproduct , Alejandro Agudelo Mira

Selective Recovery of Rare Earth Elements from Acid Mine Drainage Treatment Byproduct , Zeynep Cicek

Identification of Rockmass Deformation and Lithological Changes in Underground Mines by Using Slam-Based Lidar Technology , Francisco Eduardo Gil Hurtado

Analysis of the Brittle Failure Mechanism of Underground Stone Mine Pillars by Implementing Numerical Modeling in FLAC3D , Rosbel Jimenez

Analysis of the root causes of fatal injuries in the United States surface mines between 2008 and 2021. , Maria Fernanda Quintero

AUGMENTED REALITY AND MOBILE SYSTEMS FOR HEAVY EQUIPMENT OPERATORS IN SURFACE MINING , Juan David Valencia Quiceno

Theses/Dissertations from 2022 2022

Integrated Large Discontinuity Factor, Lamodel and Stability Mapping Approach for Stone Mine Pillar Stability , Mustafa Baris Ates

Noise Exposure Trends Among Violating Coal Mines, 2000 to 2021 , Hanna Grace Davis

Calcite depression in bastnaesite-calcite flotation system using organic acids , Emmy Muhoza

Investigation of Geomechanical Behavior of Laminated Rock Mass Through Experimental and Numerical Approach , Qingwen Shi

Static Liquefaction in Tailing Dams , Jose Raul Zela Concha

Experimental and Theoretical Investigation on the Initiation Mechanism of Low-Rank Coal's Self-Heating Process , Yinan Zhang

Development of an Entry-Scale Modeling Methodology to Provide Ground Reaction Curves for Longwall Gateroad Support Evaluation , Haochen Zhao

Size effect and anisotropy on the strength of shale under compressive stress conditions , Yun Zhao

Theses/Dissertations from 2021 2021

Evaluation of LIDAR systems for rock mass discontinuity identification in underground stone mines from 3D point cloud data , Mario Alejandro Bendezu de la Cruz

Implementing the Empirical Stone Mine Pillar Strength Equation into the Boundary Element Method Software LaModel , Samuel Escobar

Recovery of Phosphorus from Florida Phosphatic Waste Clay , Amir Eskanlou

Optimization of Operating Conditions and Design Parameters on Coal Ultra-Fine Grinding Through Kinetic Stirred Mill Tests and Numerical Modeling , Francisco Patino

The Effect of Natural Fractures on the Mechanical Behavior of Limestone Pillars: A Synthetic Rock Mass Approach Application , Mustafa Can Süner

Evaluation of Various Separation Techniques for the Removal of Actinides from A Rare Earth-Containing Solution Generated from Coarse Coal Refuse , Deniz Talan

Geology Oriented Loading Approach for Underground Coal Mines , Deniz Tuncay

Various Operational Aspects of the Extraction of Critical Minerals from Acid Mine Drainage and Its Treatment By-product , Zhongqing Xiao

Theses/Dissertations from 2020 2020

Adaptation of Coal Mine Floor Rating (CMFR) to Eastern U.S. Coal Mines , Sena Cicek

Upstream Tailings Dam - Liquefaction , Mladen Dragic

Development, Analysis and Case Studies of Impact Resistant Steel Sets for Underground Roof Fall Rehabilitation , Dakota D. Faulkner

The influence of spatial variance on rock strength and mechanism of failure , Danqing Gao

Fundamental Studies on the Recovery of Rare Earth Elements from Acid Mine Drainage , Xue Huang

Rational drilling control parameters to reduce respirable dust during roof bolting operations , Hua Jiang

Solutions to Some Mine Subsidence Research Challenges , Jian Yang

An Interactive Mobile Equipment Task-Training with Virtual Reality , Lazar Zujovic

Theses/Dissertations from 2019 2019

Fundamental Mechanism of Time Dependent Failure in Shale , Neel Gupta

A Critical Assessment on the Resources and Extraction of Rare Earth Elements from Acid Mine Drainage , Christopher R. Vass

Time-dependent deformation and associated failure of roof in underground mines , Yuting Xue

Theses/Dissertations from 2018 2018

Parametric Study of Coal Liberation Behavior Using Silica Grinding Media , Adewale Wasiu Adeniji

Three-dimensional Numerical Modeling Encompassing the Stability of a Vertical Gas Well Subjected to Longwall Mining Operation - A Case Study , Bonaventura Alves Mangu Bali

Shale Characterization and Size-effect study using Scanning Electron Microscopy and X-Ray Diffraction , Debashis Das

Behaviour Of Laminated Roof Under High Horizontal Stress , Prasoon Garg

Theses/Dissertations from 2017 2017

Optimization of Mineral Processing Circuit Design under Uncertainty , Seyed Hassan Amini

Evaluation of Ultrasonic Velocity Tests to Characterize Extraterrestrial Rock Masses , Thomas W. Edge II

A Photogrammetry Program for Physical Modeling of Subsurface Subsidence Process , Yujia Lian

An Area-Based Calculation of the Analysis of Roof Bolt Systems (ARBS) , Aanand Nandula

Developing and implementing new algorithms into the LaModel program for numerical analysis of multiple seam interactions , Mehdi Rajaeebaygi

Adapting Roof Support Methods for Anchoring Satellites on Asteroids , Grant B. Speer

Simulation of Venturi Tube Design for Column Flotation Using Computational Fluid Dynamics , Wan Wang

Theses/Dissertations from 2016 2016

Critical Analysis of Longwall Ventilation Systems and Removal of Methane , Robert B. Krog

Implementing the Local Mine Stiffness Calculation in LaModel , Kaifang Li

Development of Emission Factors (EFs) Model for Coal Train Loading Operations , Bisleshana Brahma Prakash

Nondestructive Methods to Characterize Rock Mechanical Properties at Low-Temperature: Applications for Asteroid Capture Technologies , Kara A. Savage

Mineral Asset Valuation Under Economic Uncertainty: A Complex System for Operational Flexibility , Marcell B. B. Silveira

A Feasibility Study for the Automated Monitoring and Control of Mine Water Discharges , Christopher R. Vass

Spontaneous Combustion of South American Coal , Brunno C. C. Vieira

Calibrating LaModel for Subsidence , Jian Yang

Theses/Dissertations from 2015 2015

Coal Quality Management Model for a Dome Storage (DS-CQMM) , Manuel Alejandro Badani Prado

Design Programs for Highwall Mining Operations , Ming Fan

Development of Drilling Control Technology to Reduce Drilling Noise during Roof Bolting Operations , Mingming Li

The Online LaModel User's & Training Manual Development & Testing , Christopher R. Newman

How to mitigate coal mine bumps through understanding the violent failure of coal specimens , Gamal Rashed

Theses/Dissertations from 2014 2014

Effect of biaxial and triaxial stresses on coal mine shale rocks , Shrey Arora

Stability Analysis of Bleeder Entries in Underground Coal Mines Using the Displacement-Discontinuity and Finite-Difference Programs , Xu Tang

Experimental and Theoretical Studies of Kinetics and Quality Parameters to Determine Spontaneous Combustion Propensity of U.S. Coals , Xinyang Wang

Bubble Size Effects in Coal Flotation and Phosphate Reverse Flotation using a Pico-nano Bubble Generator , Yu Xiong

Integrating the LaModel and ARMPS Programs (ARMPS-LAM) , Peng Zhang

Theses/Dissertations from 2013 2013

Column Flotation of Subbituminous Coal Using the Blend of Trimethyl Pentanediol Derivatives and Pico-Nano Bubbles , Jinxiang Chen

Applications of Surface and Subsurface Subsidence Theories to Solve Ground Control Problems , Biao Qiu

Calibrating the LaModel Program for Shallow Cover Multiple-Seam Mines , Morgan M. Sears

The Integration of a Coal Mine Emergency Communication Network into Pre-Mine Planning and Development , Mark F. Sindelar

Factors considered for increasing longwall panel width , Jack D. Trackemas

An experimental investigation of the creep behavior of an underground coalmine roof with shale formation , Priyesh Verma

Evaluation of Rope Shovel Operators in Surface Coal Mining Using a Multi-Attribute Decision-Making Model , Ivana M. Vukotic

Theses/Dissertations from 2012 2012

Calculating the Surface Seismic Signal from a Trapped Miner , Adeniyi A. Adebisi

Comprehensive and Integrated Model for Atmospheric Status in Sealed Underground Mine Areas , Jianwei Cheng

Production and Cost Assessment of a Potential Application of Surface Miners in Coal Mining in West Virginia , Timothy A. Nolan

The Integration of Geomorphic Design into West Virginia Surface Mine Reclamation , Alison E. Sears

Truck Cycle and Delay Automated Data Collection System (TCD-ADCS) for Surface Coal Mining , Patricio G. Terrazas Prado

New Abutment Angle Concept for Underground Coal Mining , Ihsan Berk Tulu

Theses/Dissertations from 2011 2011

Experimental analysis of the post-failure behavior of coal and rock under laboratory compression tests , Dachao Neil Nie

The influence of interface friction and w/h ratio on the violence of coal specimen failure , Simon H. Prassetyo

Theses/Dissertations from 2010 2010

A risk management approach to pillar extraction in the Central Appalachian coalfields , Patrick R. Bucks

The Impacts of Longwall Mining on Groundwater Systems -- A Case of Cumberland Mine Panels B5 and B6 , Xinzhi Du

Evaluation of ultrafine spiral concentrators for coal cleaning , Meng Yang

Theses/Dissertations from 2009 2009

Development of a coal reserve GIS model and estimation of the recoverability and extraction costs , Chandrakanth Reddy Apala

Application and evaluation of spiral separators for fine coal cleaning , Zhuping Che

Weak floor stability in the Illinois Basin underground coal mines , Murali M. Gadde

Design of reinforced concrete seals for underground coal mines , Rajagopala Reddy Kallu

Employing laboratory physical modeling to study the radio imaging method (RIM) , Jun Lu

Influence of cutting sequence and time effects on cutters and roof falls in underground coal mine -- numerical approach , Anil Kumar Ray

Implementing energy release rate calculations into the LaModel program , Morgan M. Sears

Modeling PDC cutter rock interaction , Ihsan Berk Tulu

Analytical determination of strain energy for the studies of coal mine bumps , Qiang Xu

Improvement of the mine fire simulation program MFIRE , Lihong Zhou

Theses/Dissertations from 2008 2008

Program-assisted analysis of the transverse pressure capacity of block stoppings for mine ventilation control , Timothy J. Batchler

Analysis of factors affecting wireless communication systems in underground coal mines , David P. McGraw

Analysis of underground coal mine refuge shelters , Mickey D. Mitchell

Theses/Dissertations from 2007 2007

Dolomite flotation of high magnesium phosphate ores using fatty acid soap collectors , Zhengxing Gu

Evaluation of longwall face support hydraulic supply systems , Ted M. Klemetti II

Experimental studies of electromagnetic signals to enhance radio imaging method (RIM) , William D. Monaghan

Analysis of water monitoring data for longwall panels , Joseph R. Zirkle

Theses/Dissertations from 2006 2006

Measurements of the electrical properties of coal measure rocks , Nikolay D. Boykov

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UKnowledge > College of Engineering > Mining Engineering > Theses & Dissertations

Theses and Dissertations--Mining Engineering

Theses/dissertations from 2024 2024.

THE METHODOLOGY FOR INTEGRATING ROBOTIC SYSTEMS IN UNDEGROUND MINING MACHINES , Peter Kolapo

DISCRETE ELEMENT MODELING TO PREDICT MUCKPILE PROFILES FROM CAST BLASTING , Russell Lamont

AUTONOMOUS SHUTTLE CAR DOCKING TO A CONTINUOUS MINER USING RGB-DEPTH IMAGERY , Sky Rose

Underground Blast Fragmentation Modeling for Use in the Mine-to-Mill Strategy , Lauren Shields

Theses/Dissertations from 2023 2023

ASSESSMENT OF AIR OVERPRESSURE FROM BLASTING USING COMPUTATIONAL FLUID DYNAMICS , Cecilia Estefania Aramayo

RECOVERY OF VALUABLE METALS FROM ELECTRONIC WASTE USING A NOVEL AMMONIA-BASED HYDROMETALLURGICAL PROCESS , Peijia Lin

AN ACID BAKING APPROACH TO ENHANCE RARE EARTH ELEMENT RECOVERY FROM BITUMINOUS COAL SOURCES , Ahmad Nawab

PREDICTION OF DYNAMIC SUBSIDENCE IN THE PROXIMITY OF LONGWALL PANEL BOUNDARIES , JESUS DAVID ROMERO BENITEZ

Prediction of Blast-Induced Ground Vibrations: A Comparison Between Empirical and Artificial-Neural-Network Approaches , Luis F. Velasquez

A LABORATORY AND NUMERICAL INVESTIGATION OF THE STRENGTH OF IRREGULARLY SHAPED PILLARS , Zachary Wedding

Theses/Dissertations from 2022 2022

DEVELOPMENT OF UNIVARIATE AND MULTIVARIATE FORECASTING MODELS FOR METHANE GAS EMISSIONS IN UNDERGROUND COAL MINES , Juan Diaz

PARAMETRIC NUMERICAL ANALYSIS OF INCLINED COAL PILLARS , Robin Flattery

Strain Energy Analysis Related To Strata Failure During Caving Operations , Caroline Gerwig

LAPTOP RECYCLING CASE STUDY: ESTIMATING THE CONTAINED VALUE AND VALUE RECOVERY PROCESS FEASIBILITY OF END-OF-LIFE CONSUMER ELECTRONICS , Zebulon Hart

INVESTIGATION INTO, & ANALYSIS OF TEMPERATURE & STRAIN DATA FOR COAL MINE SEAL MATERIAL DURING CURING , Stephanus Jaco van den Berg

Theses/Dissertations from 2021 2021

DEVELOPMENT OF AN AUTONOMOUS NAVIGATION SYSTEM FOR THE SHUTTLE CAR IN UNDERGROUND ROOM & PILLAR COAL MINES , Vasileios Androulakis

Investigation of Coal Burst Potential Using Numerical Modeling and Rock Burst Indices , Cristian David Cardenas Triana

Capture of Respirable Dust using Maintenance Free Impingement Screen , Neeraj Kumar Gupta

OXIDATION PRETREATMENT FOR ENHANCED LEACHABILITY OF RARE EARTH ELEMENTS FROM BITUMINOUS COAL SOURCES , Tushar Gupta

AN APPROACH FOR PREDICTING FLOW CHARACTERISTICS AT THE CONTINUOUS MINER FACE , Kayla Henderson

CONCEPTS FOR DEVELOPMENT OF SHUTTLE CAR AUTONOMOUS DOCKING WITH CONTINUOUS MINER USING 3-D DEPTH CAMERA , Sibley Miller

MODELING OF RARE EARTH SOLVENT EXTRACTION PROCESS FOR FLOWSHEET DESIGN AND OPTIMIZATION , Vaibhav Kumar Srivastava

Application of a Novel Ventilation Simplification Algorithm , Caitlin V. Strong

A METHODOLOGY FOR AUTONOMOUS ROOF BOLT INSTALLATION USING INDUSTRIAL ROBOTICS , Anastasia Xenaki

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Teako to acquire 90% stake in Capella’s Løkken project in Norway

Teako will issue 2.5 million common shares and pay C$350,000 in cash to Capella.

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Teako Minerals has signed a definitive agreement to acquire a 90% stake in the Løkken copper-zinc-cobalt (Cu-Zn-Co) project in Trøndelag, Norway, from Capella Minerals.

The Løkken project will be integrated with Teako’s adjacent Lomunda claims, and together with the Venna projects, they will be collectively known as the Løkken & Venna Projects.

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This consolidation represents a significant step forward for Teako, providing access to advanced drill targets, including the drill-ready Åmot target, planned for winter 2024/2025.

Teako is obligated to issue 2.5 million common shares to Capella by 30 August 2024 and pay C$350,000 in cash.

Teako will also carry out a drill programme on the Åmot target within 12 months, subject to permitting, and develop two more drill-ready targets within 24 months.

It will bear all exploration costs before deciding whether to start production.

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Should Teako opt for commercial production while Capella retains its 10% interest, a joint venture agreement will be established, detailing each party’s rights and obligations.

If Teako makes a final investment decision for production, accrued costs for Capella will be recovered by netting out 25% of Capella’s joint venture distributions until fully paid.

Should the mine close before Capella’s costs are fully paid, the remaining balance will be forgiven.

The agreement also includes co-sale rights, allowing or obligating Capella to sell its 10% interest if Teako decides to sell its stake.

Teako must offer Capella the opportunity to purchase its interest on identical terms before any sale.

The Løkken Project is subject to a 2.5% net smelter return royalty to Eurasian Minerals Sweden AB, with a buyback option of 0.5% of the royalty for $1m.

Teako will assume the annual advanced royalty payments, starting at $40,000 and increasing annually to a maximum of $75,000.

To finance the acquisition and drilling operations, Teako is conducting a private placement of up to 11.1 million common shares at C$0.09 each, aiming to raise up to C$1m.

This offering, along with the agreement’s approval, is pending acceptance by the Canadian Securities Exchange.

In 2023, Teako struck a deal to acquire a stake in Capella’s Vaddas and Birtavarre projects in northern Norway.

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