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A Weighted-Profiling Using an Ontology Basefor Semantic-Based Search
Abstract:The information on the Web increases tremendously. A number of search engines have been developed for searching Web information and retrieving relevant documents that satisfy the inquirers needs. Search engines provide inquirers irrelevant documents among search results, since the search is text-based rather than semantic-based. Information retrieval research area has presented a number of approaches and methodologies such as profiling, feedback, query modification, human-computer interaction, etc for improving search results. Moreover, information retrieval has employed artificial intelligence techniques and strategies such as machine learning heuristics, tuning mechanisms, user and system vocabularies, logical theory, etc for capturing user's preferences and using them for guiding the search based on the semantic analysis rather than syntactic analysis. Although a valuable improvement has been recorded on search results, the survey has shown that still search engines users are not really satisfied with their search results. Using ontologies for semantic-based searching is likely the key solution. Adopting profiling approach and using ontology base characteristics, this work proposes a strategy for finding the exact meaning of the query terms in order to retrieve relevant information according to user needs. The evaluation of conducted experiments has shown the effectiveness of the suggested methodology and conclusion is presented.
Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1083229Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2862
 Internet Systems Consortium (2006). ISC Internet Domain Survey.
[Online]. Available: http://www.isc.org/ops/ds/reports/2006-01
 K. Sugiyama, K. Hatano, and M. Yoshikawa, "Adaptive web search based on user profile constructed without any effort from users," in Proc. 13th ACM International Conference on World Wide Web, WWW2004, pp. 675-684, 2004.
 B. Huberman and R. Lukose, "A metasearch engine that learns which search engine to query," Science 277, pp. 535-537, 1997.
 M. Kobayashi and K. Takeda, "Information Retrieval on the Web," ACM Computing Surveys (CSUR), vol. 32, no. 2, pp. 144-173, 2000.
 Internet World Stats: Usage and Population Statistics (2006). Internet Growth Statistics.
[Online]. Available: http://www.internetworldstats.com/emarketing.htm
 V. C. J. Rijsbergen, Information Retrieval (2nd ed.). Computer Laboratory, University of Cambridge. Butter Worths, London, 1979, pp. 1-12.
[Online]. Available: http://www.dcs.gla.ac.uk/~iain/keith/
 D. C. Blair, "The data-document distinction revisited," ACM SIGMIS Database, vol. 37, no. 1, pp. 77-96, 2006.
 E. A. Stephen, The Google Legacy: How Google's Internet Search is Transforming Application Software. Tetbury, England, 2005, Chapter 3: Google Technology.
[Online]. Available: http://www.infonortics.com/publications/google/technology.pdf
 Google Corporate Information, Google Milestones, 2006,
[Online]. Available: http://www.google.com/corporate/history.html
 J. Battelle, (2005, August). The Birth of Google, Wired Magazine, Issue 13.08.
[Online]. Available: http://www.wired.com/wired/archive/13.08/battelle.html
 S. Brin and L. Page, "The anatomy of a large-scale hypertextual Web search engines," in Proc. 7th International World Wide Web Conference, Computer Networks and ISDN Systems, 1998, vol. 30, no. 1-7, pp. 107- 117.
 W. Meng, Z. Wu, C. Yu, and Z. Li, "A highly scalable and effective method for metasearch," ACM Transactions on Information Systems (TOIS), vol. 19, no. 3, pp. 310-335, 2001.
 K. C. Chang, B. He, C. Li, M. Patel, and Z. Zhang, "Structured databases on the Web: Observations and implications," ACM SIGMOD, vol. 33, no. 3, pp. 61-70, 2004.
 SearchEngineWatch.com. (2005). Metacrawlers and Metasearch Engines.
[Online]. Available: http://searchenginewatch.com/links/article.php/2156241
 A. L├│pez-Ortiz, "Search engines and Web information retrieval," Lecture Notes in Computer Science LNCS, Springer-Verlag Berlin/Heidelberg, vol. 3405/2005, pp. 183-191, 2005.
 S. Mizzaro, "Relevance: the whole history," Journal of the American Society for Information Science (JASIS), 48(9), pp. 810-832, 1996.
 S. H. Myaeng and R. R. Korfhage, "Towards an intelligent and personalized retrieval system," in Proc. of the ACM SIGART International Symposium on Methodologies for Intelligent Systems, Knoxville, Tennessee, United States, pp. 121-129, 1986.
 W. Meng, C. Yu, and K. Liu, "Building efficient and effective metasearch engines," ACM Computing Surveys (CSUR), vol. 34, no. 1, pp. 48-89, 2002.
 G. G. Chowdhury, Introduction to Modern Information Retrieval. Library Association Publishing, London, 1999.
 B. V. Gils and E. D. Schabell, "User-profiles for information retrieval," in Proc. 15th Belgian-Dutch Conference on Artificial Intelligence (BNAIC-03), Nijmegen, Netherlands, 2003.
[Online]. Available: http://citeseer.ist.psu.edu/vangils03userprofiles.html
 H. B. Styltsvig, "Ontology-based information retrieval," Ph.D. dissertation, Dept. Comp. Sc., Roskilde University, Denmark, 2006.
 S. K. Bhatia, J. S. Deogun, and V. V. Raghavan, "User profiles for information retrieval," in Proc. 6th International Symposium on Methodologies for Intelligent Systems (ISMIS), Springer-Verlag Berlin / Heidelberg, 1991, Vol. 542, pp. 102-111.
 C. Danilowicz and H. C. Nguyen, "Using user profiles in intelligent information retrieval," in Proc. 13th International Symposium on Methodologies for Intelligent Systems (ISMIS), LNAI, Springer-Verlag Berlin/Heidelberg, 2002, Vol. 2366, pp. 223-231.
 B. V. Gils, E. Proper, and P. V. Bommel, "Towards a general theory for information supply," in Proc. 10th International Conference on Human- Computer Interaction, 2003.
 P. M. Chen and F. C. Kuo, "An information retrieval system based on a user profile," ACM, Journal of Systems and Software, 54(1), pp. 3-8, 2000.
 D. H. Widyantoro, J. Yin, M. Seif El-Nasr, L. Yang, A. Zacchi, and J. Yen, "Alipes: A swift messenger in cyberspace," in AAAI-99 Spring Symposium on Intelligent Agent in Cyberspace, pp. 62-67, 1999.
 D. H. Widyantoro, T. R. Ioerger, and J. Yen, "An adaptive algorithm for learning changes in user interests," in Proc. 8th International Conference on Information and Knowledge Management CIKM -99, 1999, pp. 405-412.
 A. Pretschner and S. Gauch, "Ontology based personalized search," in Proc. 11th IEEE International Conference on Tools with Artificial Intelligence (ICTAI), Nov. 1999, pp. 391-398.
 S. Gauch, M. Speretta, and A. Pretschner, "Ontology-based user profiles for personalized search," Integrated Series in Information Systems, SpringerLink, Vol. 14, pp. 665-694, 2007.
 The Open Directory Project (ODP), 2004.
[Online] Available: http://dmoz.org
 V. Challam, "Ontology-based user profiles for contextual search," M.S. thesis, Kansas Univ., Lawrence, KS, Germany, 2004.
 A. G├│mez-Pérez, M. Fern├índez-L├│pez, and O. Corcho, Ontological Engineering (2nd ed.). Springer-Verlag London Limited, England, 2004, pp. 1-5.
 B. Thuraisingham, XML Databases and the Semantic Web (1st ed.). CRC Press, USA, 2000, pp. 109-111.
 G. Antoniou and G. van Harmelen, Semantic Web Primer (1st ed.). The MIT press, Cambridge, Massachusetts, London, 2004, pp. 7-9; 193-194.
 J. T. Pollock and R. Hodgson, Adaptive information: Improving business through semantic interoperability, Grid Computing, and Enterprise Integration, (Wiley Series in Systems Engineering and Management), Wiley-Interscience, 2004.
 A. Singh and K. Nakata, "Hierarchical classification of Web search results using personalized ontologies," in Proc. 3rd International Conference on Universal Access in Human-Computer Interaction, HCI International 2005, Las Vegas, NV, 2005.
 F. Liu, C. Yu, and W. Meng, "Personalized Web search for improving retrieval effectiveness," IEEE Transactions on Knowledge and Data Engineering, 16 (1), pp. 28-40, 2004.
 Y. Li and N. Zhong, "Mining Ontology for automatically acquiring Web user information needs," IEEE Transactions on Knowledge and Data Engineering, vol. 18, pp. 554-568, 2006.
 X. Zhou, S. T. Wu, Y. Li, Y. Xu, R. Lau, and P. Bruza, "Utilizing search intent in topic ontology-based user profile for Web mining," in 2006 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2006 Main Conference Proceedings)(WI'06), 2006, pp. 558-564.
 S. T. Wu, Y. Li, Y. Xu, B. Pham, and P. Chen, "Automatic patterntaxonomy extraction for Web mining," presented at the 2004 IEEE ACM International Conference on Web Intelligence, WIC, Beijing, China, 2004.
 X. Zhou, Y. Li, Y. Xu, and R. Lau, "Relevance assessment of topic ontology," presented at the Fourth International Conference on Active Media Technology. Brisbane, Australia, 2006.
 H. Zhang, Y. Song, and H. T. Song, "Construction of ontology-based user model for Web personalization," User Modeling (UM'07), LNCS, Springer-Verlag Berlin/Heidelberg, vol. 4511, pp. 67-76, 2007.
 J. Trajkova and S. Gauch, "Improving ontology-based user profiles," in Proc. of the Recherche d'Information Assist e par Ordinateur. RIAO 2004, Vaucluse, France, 2004, pp. 380-389.
 A. Sieg, B. Mobasher, and R. Burke, "Representing context in Web search with ontological user profiles," CONTEXT 2007, LNAI, Springer- Verlag Berlin/Heidelberg , vol. 4635, pp. 439-452, 2007.
 H. AbdEl-el-Jaber and T. Sembok, "A bivalent-profiling using an ontology base for semantic-based search," JASIST, submitted for publication.