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Academic literature on the topic 'Search engine'
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Journal articles on the topic "Search engine":
Manjula, D., and T. V. Geetha. "Semantic Search Engine." Journal of Information & Knowledge Management 03, no. 01 (March 2004): 107–17. http://dx.doi.org/10.1142/s0219649204000729.
Lee, Sungin, Wonhong Jang, Eunsol Lee, and Sam G. Oh. "Search engine optimization." Library Hi Tech 34, no. 2 (June 20, 2016): 197–206. http://dx.doi.org/10.1108/lht-02-2016-0014.
Goyal, Harsh, and Komal kapoor. "Search Engine Optimization with Google." International Journal for Research in Applied Science and Engineering Technology 10, no. 12 (December 31, 2022): 496–501. http://dx.doi.org/10.22214/ijraset.2022.47904.
Li, Yi, Zhihui Yuan, Yujie Li, and Jing Liu. "Factors influencing search engine usage behavior." Social Behavior and Personality: an international journal 46, no. 1 (January 9, 2018): 1–10. http://dx.doi.org/10.2224/sbp.6211.
Stevenson, Valerie. "Search Engine Update." Legal Information Management 1, no. 3 (2001): 28–31. http://dx.doi.org/10.1017/s1472669600000566.
Radadiya, Jitendrakumar P., Kalpesh Rasiklal Rakholiya, and Dr Dhaval R. Kathiriya. "Intelligent Sementic Web Search Engine." International Journal of Scientific Research 1, no. 7 (June 1, 2012): 34–35. http://dx.doi.org/10.15373/22778179/dec2012/13.
de Cornière, Alexandre. "Search Advertising." American Economic Journal: Microeconomics 8, no. 3 (August 1, 2016): 156–88. http://dx.doi.org/10.1257/mic.20130138.
Takama, Yasufumi, Yanjun Zhu, Shogo Kori, Koichi Yamaguchi, Lieu-Hen Chen, and Hiroshi Ishikawa. "Design of Context Search Engine Based on Analysis of User’s Search Intentions." Journal of Advanced Computational Intelligence and Intelligent Informatics 20, no. 6 (November 20, 2016): 910–18. http://dx.doi.org/10.20965/jaciii.2016.p0910.
Bukhor, Saiful i. "Analisis Perbandingan Fitur Search Engine." INFORMAL: Informatics Journal 3, no. 1 (February 25, 2019): 17. http://dx.doi.org/10.19184/isj.v3i1.9850.
Sharma, Dilip Kumar, and A. K. Sharma. "Search Engine." International Journal of Information Communication Technologies and Human Development 3, no. 2 (April 2011): 38–51. http://dx.doi.org/10.4018/ijicthd.2011040103.
Dissertations / Theses on the topic "Search engine":
Blaauw, Pieter. "Search engine poisoning and its prevalence in modern search engines." Thesis, Rhodes University, 2013. http://hdl.handle.net/10962/d1002037.
Fahlström, Kamilla, and Caroline Jensen. "Search Engine Marketing in SMEs : The motivations behind using search engine marketing." Thesis, Högskolan i Gävle, Avdelningen för ekonomi, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-21116.
Hurlock, Jonathan. "Twitter search : building a useful search engine." Thesis, Swansea University, 2015. https://cronfa.swan.ac.uk/Record/cronfa43037.
Narayan, Nitesh. "Advanced Intranet Search Engine." Thesis, Mälardalen University, School of Innovation, Design and Engineering, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-9408.
Information retrieval has been a prevasive part of human society since its existence.With the advent of internet and World wide Web it became an extensive area of researchand major foucs, which lead to development of various search engines to locate the de-sired information, mostly for globally connected computer networks viz. internet.Butthere is another major part of computer network viz. intranet, which has not seen muchof advancement in information retrieval approaches, in spite of being a major source ofinformation within a large number of organizations.Most common technique for intranet based search engines is still mere database-centric. Thus practically intranets are unable to avail the beneﬁts of sophisticated tech-niques that have been developed for internet based search engines without exposing thedata to commercial search engines.In this Master level thesis we propose a ”state of the art architecture” for an advancedsearch engine for intranet which is capable of dealing with continuously growing sizeof intranets knowledge base. This search engine employs lexical processing of doc-umetns,where documents are indexed and searched based on standalone terms or key-words, along with the semantic processing of the documents where the context of thewords and the relationship among them is given more importance.Combining lexical and semantic processing of the documents give an effective ap-proach to handle navigational queries along with research queries, opposite to the modernsearch engines which either uses lexical processing or semantic processing (or one as themajor) of the documents. We give equal importance to both the approaches in our design,considering best of the both world.This work also takes into account various widely acclaimed concepts like inferencerules, ontologies and active feedback from the user community to continuously enhanceand improve the quality of search results along with the possibility to infer and deducenew knowledge from the existing one, while preparing for the advent of semantic web.
King, John D. "Search engine content analysis." Queensland University of Technology, 2008. http://eprints.qut.edu.au/26241/.
Edlund, Joakim. "Cognitive Search Engine Optimization." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-281882.
King, John Douglas. "Search engine content analysis." Thesis, Queensland University of Technology, 2008. https://eprints.qut.edu.au/26241/1/John_King_Thesis.pdf.
Khan, Saiful. "Visualization assisted enterprise search engine." Thesis, University of Oxford, 2015. https://ora.ox.ac.uk/objects/uuid:d1790b99-c30e-487b-b87e-98d4e3a8b2bb.
Slavík, Michal. "Search Engine Marketing neziskových organizací." Master's thesis, Vysoká škola ekonomická v Praze, 2010. http://www.nusl.cz/ntk/nusl-124602.
FISTER, JUSTIN M. "CORRELATION ANALYSIS OF ON-PAGE ATTRIBUTES AND SEARCH ENGINE RANKINGS." University of Cincinnati / OhioLINK, 2007. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1178730597.
Books on the topic "Search engine":
Davis, Harold. Search engine optimization . [Calif.]: O'Reilly, 2006.
Clay, Bruce. Search Engine Optimization . Hoboken: For Dummies [Imprint], 2009.
Ossip, Kathleen. The Search Engine . Philadelphia, USA: American Poetry Review, 2002.
Halavais, Alexander M. Campbell. Search engine society . Cambridge: Polity, 2009.
Ramos, Andreas. Search Engine Marketing . New York: McGraw-Hill, 2008.
Ramos, Andreas. Search engine marketing . New York: McGraw-Hill, 2009.
Thurow, Shari. Search engine visibility . Indianapolis, Ind: New Riders, 2003.
Thurow, Shari. Search engine visibility . 2nd ed. Berkeley, CA: New Riders, 2008.
Grappone, Jennifer. Search Engine Optimization . New York: John Wiley & Sons, Ltd., 2008.
Ledford, Jerri L. Search Engine Optimization . 2nd ed. Hoboken: Wiley [Imprint], 2009.
Book chapters on the topic "Search engine":
Weik, Martin H. "search engine." In Computer Science and Communications Dictionary , 1528. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_16727.
Das, Subhankar. "Search Engine Algorithm and Search Engine Marketing." In Search Engine Optimization and Marketing , 117–80. First edition. | Boca Raton : CRC Press, 2021.: Chapman and Hall/CRC, 2020. http://dx.doi.org/10.1201/9780429298509-6.
Thelwall, Michael. "Automatic Search Engine Searches: LexiURL Searcher." In Introduction to Webometrics: Quantitative Web Research for the Social Sciences , 57–70. Cham: Springer International Publishing, 2009. http://dx.doi.org/10.1007/978-3-031-02261-6_5.
Goldman, E. "Search Engine Bias and the Demise of Search Engine Utopianism." In Web Search , 121–33. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-75829-7_8.
Lieberam-Schmidt, Sönke. "Search Engine Optimization." In Analyzing and Influencing Search Engine Results , 163–203. Wiesbaden: Gabler, 2010. http://dx.doi.org/10.1007/978-3-8349-8915-4_5.
Carterette, Ben. "Search Engine Metrics." In Encyclopedia of Database Systems , 1–6. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4899-7993-3_325-2.
Van Looy, Amy. "Search Engine Optimization." In Social Media Management , 113–32. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-21990-5_6.
Li, Mingjing, and Wei-Ying Ma. "Image Search Engine." In Encyclopedia of Multimedia , 335–37. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-78414-4_81.
West, Adrian W. "Search Engine Optimization." In Practical Web Design for Absolute Beginners , 169–82. Berkeley, CA: Apress, 2016. http://dx.doi.org/10.1007/978-1-4842-1993-5_19.
Hassan, Nihad A., and Rami Hijazi. "Search Engine Techniques." In Open Source Intelligence Methods and Tools , 127–201. Berkeley, CA: Apress, 2018. http://dx.doi.org/10.1007/978-1-4842-3213-2_4.
Conference papers on the topic "Search engine":
Arkhipova, Olga, Lidia Grauer, Igor Kuralenok, and Pavel Serdyukov. "Search Engine Evaluation based on Search Engine Switching Prediction." In SIGIR '15: The 38th International ACM SIGIR conference on research and development in Information Retrieval . New York, NY, USA: ACM, 2015. http://dx.doi.org/10.1145/2766462.2767786.
Knok, Zeljko, and Mark Marcec. "Universtiy search engine." In 2016 39th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO) . IEEE, 2016. http://dx.doi.org/10.1109/mipro.2016.7522267.
Zhang, Jie, Xiong Zhang, and Wei Zhang. "Microseismic search engine." In SEG Technical Program Expanded Abstracts 2013 . Society of Exploration Geophysicists, 2013. http://dx.doi.org/10.1190/segam2013-1277.1.
Aldweik, Ghadeer, Saadia Malik, Abrar Almuhammidi, Wejdan Alyoubi, Ahad Alsulami, and Hind Al-Oufi. "PHARMACEUTICAL SEARCH ENGINE." In International Conference on e-Society 2020 . IADIS Press, 2020. http://dx.doi.org/10.33965/es2020_202005l011.
Kamath, Abhirup, Siddhesh Menon, Archita Poddar, Vijay Katkar, and Savita Lohiya. "Programmer's Search Engine." In 2019 International Conference on Advances in Computing, Communication and Control (ICAC3) . IEEE, 2019. http://dx.doi.org/10.1109/icac347590.2019.9036840.
Rajkumar, N., B. Gohin, and V. Vinod. "Search engine: intelligent web service search." In IET Chennai 3rd International Conference on Sustainable Energy and Intelligent Systems (SEISCON 2012) . Institution of Engineering and Technology, 2012. http://dx.doi.org/10.1049/cp.2012.2183.
Fagroud, Fatima Zahra, El Habib Ben Lahmar, Mohamed Amine, Hicham Toumi, and Sanaa El Filali. "What does mean search engine for IOT or IOT search engine." In BDIoT'19: The 4th International Conference On Big Data and Internet of Things . New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3372938.3372958.
Kumar, Rajesh, Sunil Kumar Singh, and Virendra Kumar. "A heuristic approach for search engine selection in meta-search engine." In 2015 International Conference on Computing, Communication & Automation (ICCCA) . IEEE, 2015. http://dx.doi.org/10.1109/ccaa.2015.7148496.
Schultz, Carsten D. "SEARCH TRIANGLE: INTEGRATING SEARCH INTENTION IN SEARCH ENGINE ADVERTISING." In Bridging Asia and the World: Global Platform for Interface between Marketing and Management . Global Alliance of Marketing & Management Associations, 2016. http://dx.doi.org/10.15444/gmc2016.12.01.02.
Zhu, Yunzhang, Gang Wang, Junli Yang, Dakan Wang, Jun Yan, Jian Hu, and Zheng Chen. "Optimizing search engine revenue in sponsored search." In the 32nd international ACM SIGIR conference . New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1571941.1572042.
Reports on the topic "Search engine":
Aldrich, Susan. Northern Light Enterprise Search Engine V.3.0 . Boston, MA: Patricia Seybold Group, June 2005. http://dx.doi.org/10.1571/pr6-23-05cc.
Aldrich, Susan. Who Needs a Premium Product Search Engine? Boston, MA: Patricia Seybold Group, January 2004. http://dx.doi.org/10.1571/psgp1-9-04cc.
Aldrich, Susan. Five Steps in Selecting a Search Engine . Boston, MA: Patricia Seybold Group, October 2008. http://dx.doi.org/10.1571/psgp10-23-08cc.
Seacord, Robert C., Scott A. Hissam, and Kurt C. Wallnau. Agora: A Search Engine for Software Components . Fort Belvoir, VA: Defense Technical Information Center, August 1998. http://dx.doi.org/10.21236/ada351653.
Aldrich, Susan. Search Engine Marketing and Optimization Wisdom V.2003 . Boston, MA: Patricia Seybold Group, December 2003. http://dx.doi.org/10.1571/psgp12-19-03cc.
Adams, Paige, Pranav Anand, Grant Gehrke, Ralucca Gera, Marco Draeger, Craig Martell, and Kevin Squire. ReSEARCH: A Requirements Search Engine: Progress Report 2 . Fort Belvoir, VA: Defense Technical Information Center, September 2008. http://dx.doi.org/10.21236/ada529465.
Ramos, Lionel R. Hardware Realization of an Ethernet Packet Analyzer Search Engine . Fort Belvoir, VA: Defense Technical Information Center, June 2000. http://dx.doi.org/10.21236/ada392128.
Mager, Astrid, ed. Search engine imaginary - Visions and values in the co-production of search technology and Europe . Vienna: self, 2018. http://dx.doi.org/10.1553/ita-pa-am-2017.
Cuevas, Leslie M., Jewon Lyu, and Heejin Lim. Instagram As a Search Engine: Can Browsers Convert to Shoppers? Ames: Iowa State University, Digital Repository, 2017. http://dx.doi.org/10.31274/itaa_proceedings-180814-295.
Hawkins, Brian M. Developing a Modular Framework for Implementing a Semantic Search Engine . Fort Belvoir, VA: Defense Technical Information Center, February 2010. http://dx.doi.org/10.21236/ada555393.
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(updated 2023-06-28) A few days ago, we discussed the new dataset publications in dblp. As a preparation for more and more detailed datasets we slightly modify the DTD that defines the structure of our XML data export. A quick reminder: you can download the dblp dataset as a single XML […]
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The top list of academic search engines
Academic search engines have become the number one resource to turn to in order to find research papers and other scholarly sources. While classic academic databases like Web of Science and Scopus are locked behind paywalls, Google Scholar and others can be accessed free of charge. In order to help you get your research done fast, we have compiled the top list of free academic search engines.
- 1. Google Scholar
Google Scholar is the clear number one when it comes to academic search engines. It's the power of Google searches applied to research papers and patents. It not only lets you find research papers for all academic disciplines for free but also often provides links to full-text PDF files.
- Coverage: approx. 200 million articles
- Abstracts: only a snippet of the abstract is available
- Related articles: ✔
- References: ✔
- Cited by: ✔
- Links to full text: ✔
- Export formats: APA, MLA, Chicago, Harvard, Vancouver, RIS, BibTeX
BASE is hosted at Bielefeld University in Germany. That is also where its name stems from (Bielefeld Academic Search Engine).
- Coverage: approx. 136 million articles (contains duplicates)
- Abstracts: ✔
- Related articles: ✘
- References: ✘
- Cited by: ✘
- Export formats: RIS, BibTeX
CORE is an academic search engine dedicated to open-access research papers. For each search result, a link to the full-text PDF or full-text web page is provided.
- Coverage: approx. 136 million articles
- Links to full text: ✔ (all articles in CORE are open access)
- Export formats: BibTeX
- 4. Science.gov
Science.gov is a fantastic resource as it bundles and offers free access to search results from more than 15 U.S. federal agencies. There is no need anymore to query all those resources separately!
- Coverage: approx. 200 million articles and reports
- Links to full text: ✔ (available for some databases)
- Export formats: APA, MLA, RIS, BibTeX (available for some databases)
- 5. Semantic Scholar
Semantic Scholar is the new kid on the block. Its mission is to provide more relevant and impactful search results using AI-powered algorithms that find hidden connections and links between research topics.
- Coverage: approx. 40 million articles
- Export formats: APA, MLA, Chicago, BibTeX
- 6. Baidu Scholar
Although Baidu Scholar's interface is in Chinese, its index contains research papers in English as well as Chinese.
- Coverage: no detailed statistics available, approx. 100 million articles
- Abstracts: only snippets of the abstract are available
- Export formats: APA, MLA, RIS, BibTeX
RefSeek searches more than one billion documents from academic and organizational websites. Its clean interface makes it especially easy to use for students and new researchers.
- Coverage: no detailed statistics available, approx. 1 billion documents
- Abstracts: only snippets of the article are available
- Export formats: not available
- Frequently Asked Questions about academic search engines
Google Scholar is an academic search engine, and it is the clear number one when it comes to academic search engines. It's the power of Google searches applied to research papers and patents. It not only let's you find research papers for all academic disciplines for free, but also often provides links to full text PDF file.
Semantic Scholar is a free, AI-powered research tool for scientific literature developed at the Allen Institute for AI. Sematic Scholar was publicly released in 2015 and uses advances in natural language processing to provide summaries for scholarly papers.
BASE , as its name suggest is an academic search engine. It is hosted at Bielefeld University in Germany and that's where it name stems from (Bielefeld Academic Search Engine).
CORE is an academic search engine dedicated to open access research papers. For each search result a link to the full text PDF or full text web page is provided.
Science.gov is a fantastic resource as it bundles and offers free access to search results from more than 15 U.S. federal agencies. There is no need any more to query all those resources separately!
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