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Search Engines Going beyond Keyword Search: A Survey

by Mahmudur Rahman
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 75 - Number 17
Year of Publication: 2013
Authors: Mahmudur Rahman
10.5120/13200-0357

Mahmudur Rahman . Search Engines Going beyond Keyword Search: A Survey. International Journal of Computer Applications. 75, 17 ( August 2013), 1-8. DOI=10.5120/13200-0357

@article{ 10.5120/13200-0357,
author = { Mahmudur Rahman },
title = { Search Engines Going beyond Keyword Search: A Survey },
journal = { International Journal of Computer Applications },
issue_date = { August 2013 },
volume = { 75 },
number = { 17 },
month = { August },
year = { 2013 },
issn = { 0975-8887 },
pages = { 1-8 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume75/number17/13200-0357/ },
doi = { 10.5120/13200-0357 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:44:29.896517+05:30
%A Mahmudur Rahman
%T Search Engines Going beyond Keyword Search: A Survey
%J International Journal of Computer Applications
%@ 0975-8887
%V 75
%N 17
%P 1-8
%D 2013
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In order to solve the problem of information overkill on the web or large domains, current information retrieval tools especially search engines need to be improved. Much more intelligence should be embedded to search tools to manage the search and filtering processes effectively and present relevant information. As the web swells with more and more data, the predominant way of sifting through all of that data —keyword search —will one day break down in its ability to deliver the exact information people want at our fingertips. Hence search engines are trying to break the shackles of the concept of keyword search what typically most search engines do. This paper tries to identify the major challenges for today's keyword search engines to adapt with the fast growth of web and support comprehensive user demands in quick time. Then it surveys different non-keyword based paradigms proposed, developed or implemented by researchers and different search engines and also classifies those approaches according to the features focused by the different search engines to deliver results.

References
  1. Jeffrey R. Bach, Charles Fuller, Amarnath Gupta, Arun Hampapur, Bradley Horowitz, Rich Humphrey, Ramesh C. Jain, and Chiao-Fe Shu. Virage image search engine: an open framework for image management. pages 76–87, 1996.
  2. Ravish Bhagdev, Sam Chapman, Fabio Ciravegna, Vitaveska Lanfranchi, and Daniela Petrelli. Hybrid search: effectively combining keywords and semantic searches. In Proceedings of the 5th European semantic web conference on The semantic web: research and applications, ESWC'08, pages 554–568, Berlin, Heidelberg, 2008. Springer-Verlag.
  3. Deepavali Bhagwat and Neoklis Polyzotis. Searching a file system using inferred semantic links. In Proceedings of the sixteenth ACM conference on Hypertext and hypermedia, HYPERTEXT '05, pages 85–87, NY, USA, 2005. ACM.
  4. Piximilar: Image by color. http: //research. cs. wisc. edu/vision/piximilar/.
  5. Shih-Fu Chang, W. Chen, H. J. Meng, H. Sundaram, and Di Zhong. A fully automated content-based video search engine supporting spatiotemporal queries. Circuits and Systems for Video Technology, IEEE Transactions on, 8(5):602–615, 1998.
  6. Shih-Fu Chang, Lyndon S. Kennedy, and Eric Zavesky. Columbia university's semantic video search engine. In Proceedings of the 6th ACM international conference on Image and video retrieval, CIVR '07, pages 643–643, NY, USA, 2007. ACM.
  7. Roger H. L. Chiang, Cecil Eng Huang Chua, and Veda C. Storey. A smart web query method for semantic retrieval of web data. Data Knowl. Eng. , 38(1):63–84, July 2001.
  8. DeepDyve. http://www. deepdyve. com/.
  9. Li Ding, Tim Finin, Anupam Joshi, Rong Pan, R. Scott Cost, Yun Peng, Pavan Reddivari, Vishal Doshi, and Joel Sachs. Swoogle: a search and metadata engine for the semantic web. In Proceedings of the thirteenth ACM international conference on Information and knowledge management, CIKM '04, pages 652–659, NY, USA, 2004. ACM.
  10. M. Dittenbach, H. Berger, and D. Merkl. Automated concept discovery from web resources. In Web Intelligence, 2006. WI 2006. IEEE/WIC/ACM International Conference on, pages 309–312, 2006.
  11. WolframAlpha: Computational Knowledge Engine. http://www. wolframalpha. com/.
  12. M. Flickner, H. Sawhney, W. Niblack, J. Ashley, Qian Huang, B. Dom, M. Gorkani, J. Hafner, D. Lee, D. Petkovic, D. Steele, and P. Yanker. Query by image and video content: the qbic system. Computer, 28(9):23–32, 1995.
  13. Thomas Funkhouser, Patrick Min, Michael Kazhdan, Joyce Chen, Alex Halderman, David Dobkin, and David Jacobs. A search engine for 3d models. ACM Trans. Graph. , 22(1):83–105, January 2003.
  14. Hakia. http://company. hakia. com/.
  15. David F. Huynh, David R. Karger, and Robert C. Miller. Exhibit: lightweight structured data publishing. In Proceedings of the 16th international conference on World Wide Web, WWW '07, pages 737–746, NY, USA, 2007. ACM.
  16. IBM. Informix excalibur text search datablade. http://www-01. ibm. com/software/data/ informix/blades/excaliburtext/.
  17. Eser Kandogan, Rajasekar Krishnamurthy, Sriram Raghavan, Shivakumar Vaithyanathan, and Huaiyu Zhu. Avatar semantic search: a database approach to information retrieval. In Proceedings of the 2006 ACM SIGMOD international conference on Management of data, SIGMOD '06, pages 790–792, NY, USA, 2006. ACM.
  18. Wei-Po Lee and Tsung-Che Tsai. An interactive agent-based system for concept-based web search. Expert Systems with Applications, 24(4):365 – 373, 2003.
  19. Zhusong Liu and Yuqin Zhang. Research and design of e-commerce semantic search. In Information Management, Innovation Management and Industrial Engineering (ICIII), 2010 International Conference on, volume 4, pages 332–334, 2010.
  20. Gary Marchionini. Exploratory search: from finding to understanding. Commun. ACM, 49(4):41–46, April 2006.
  21. LookSmart Search Marketing. http://search. looksmart. com/.
  22. Paul Miller. Powerset shows semantic search solution. http://www. zdnet. com/blog/semantic-web/ powerset-shows-semantic-search-solution/141, May 2008.
  23. MrTaggy. http://mrtaggy. com/.
  24. Open Directory Project. http://www. dmoz. org/about. html.
  25. RevIMG. http://www. revimg. com/.
  26. Dogpile Web Search. http://www. dogpile. com/.
  27. TinEye Reverse Image Search. http://www. tineye. com/.
  28. Nova spivack. The road to semantic search the twine. com story. http://www. novaspivack. com/uncategorized/ the-road-to-semantic-search-the-twine-com-story, December 2009.
  29. G. N. Fanzou Tchuissang, Xu De, N. Wang, and Franc¸ois Siewe. Xirs: an xml-based image retrieval system. In Proceedings of the 7th Conference on 7th WSEAS International Conference on Multimedia, Internet & Video Technologies - Volume 7, MIV'07, pages 233–238, Stevens Point, Wisconsin, USA, 2007. World Scientific and Engineering Academy and Society (WSEAS).
  30. SenseBot: The Search Engine that finds sense in a heap of Web pages. http://www. sensebot. net/.
  31. MetaCrawler: Search the Search Engines. http://www. metacrawler. com/.
  32. Michal Tvaro¡zek and M´aria Bielikov´a. Collaborative multi-paradigm exploratory search. In Proceedings of the hypertext 2008 workshop on Collaboration and collective intelligence, WebScience '08, pages 29–33, NY, USA, 2008. ACM.
  33. Max L. Wilson, Bill Kules, m. c. schraefel, and Ben Shneiderman. From keyword search to exploration: Designing future search interfaces for the web. Found. Trends Web Sci. , 2(1):1–97, January 2010.
  34. Ka-Ping Yee, Kirsten Swearingen, Kevin Li, and Marti Hearst. Faceted metadata for image search and browsing. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, CHI '03, pages 401–408, NY, USA, 2003. ACM.
  35. Junliang Zhang and Gary Marchionini. Evaluation and evolution of a browse and search interface: Relation browser++. In Proceedings of the 2005 national conference on Digital government research, dg. o '05, pages 179–188. Digital Government Society of North America, 2005.
  36. Guobing Zou, Bofeng Zhang, Yanglan Gan, and Jianwen Zhang. An ontology-based methodology for semantic expansion search. In Fuzzy Systems and Knowledge Discovery, 2008. FSKD '08. Fifth International Conference on, volume 5, pages 453–457, 2008.
Index Terms

Computer Science
Information Sciences

Keywords

keyword based search semantic web search search engine computational knowledge engine question-answering system

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