Abstract
This paper addresses the problems of extracting instances from the Deep Web, enriching a domain specific ontology with those instances, and using this ontology to improve Web search. Extending an existing ontology with a large number of instances extracted from the Deep Web is an important process for making the ontology more usable for indexing of Deep Web sites. We demonstrate how instances extracted from the Deep Web are used to enhance a domain ontology. We show the contribution of the enriched ontology to Web search effectiveness. This is done by comparing the number of relevant Web sites returned by a search engine with a user’s search terms only, with the Web sites found when using additional ontology-based search terms. Experiments suggest that the ontology plus instances approach results in more relevant Web sites among the first 100 hits.
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References
Singh, M.P.: Deep Web structure. IEEE Internet Computing 6(5), 4-5 (September 2002)
He, B., Patel, M., Zhang, Z., Chang, K.C.-C.: Accessing the Deep Web: A Survey. Communications of the ACM (CACM) 50(5), 94–101 (2007)
Ntoulas, A., Zerfos, P., Cho, J.: Downloading Textual Hidden Web Content Through Keyword Queries. In: Proc. of the ACM/IEEE Joint Conf. on Digital Libraries (JCDL), pp. 100–109 (2005)
Gruber, T.R.: Toward principles for the design of ontologies used for knowledge sharing. International Journal of Human-Computer Studies 43(5), 907–928 (1995)
Davulcu, H., Vadrevu, S., Nagarajan, S., Ramakrishnan, I.V.: OntoMiner: bootstrapping and populating ontologies from domain-specific Web sites. IEEE Intelligent Systems 18(5), 24–33 (2003)
McDowell, L.K., Cafarella, M.: Ontology-driven Information Extraction with OntoSyphon. In: Cruz, I., Decker, S., Allemang, D., Preist, C., Schwabe, D., Mika, P., Uschold, M., Aroyo, L.M. (eds.) ISWC 2006. LNCS, vol. 4273, pp. 428–444. Springer, Heidelberg (2006)
An, Y.J., Geller, J., Wu, Y.-T., Chun, S.A.: Semantic Deep Web: Automatic Attribute Extraction from the Deep Web Data Sources. In: Proc. of the 22nd Annual ACM Symposium on Applied Computing (SAC 2007), Seoul, Korea (March 2007)
Dou, D., McDermott, D.V., Qi, P.: Ontology Translation on the Semantic Web. Journal on Data Semantics 2, 35–57 (2005)
Wu, W., Doan, A., Yu, C.T., Meng, W.: Bootstrapping Domain Ontology for Semantic Web Services from Source Web Sites. In: Bussler, C.J., Shan, M.-C. (eds.) TES 2005. LNCS, vol. 3811, pp. 11–22. Springer, Heidelberg (2006)
An, Y.J., Geller, J., Wu, Y.-T., Chun, S.A.: Automatic Generation of Ontology from the Deep Web. In: Proceedings of 6th International Workshop on Web Semantics (WebS 2007), September 3-7, 2007 (in Press, 2007)
Stanford Medical Informatics, Protégé 3.2.5 [Computer program API] (Retrieved, May 2007), http://protege.stanford.edu/doc/pdk/api/index.html
Stanford Medical Informatics, Protégé - OWL 3.2.1 [Computer program API] (Retrieved, May 2007), http://protege.stanford.edu/download/release-javadoc-owl/
Jansen, B.J., Spink, A., Saracevic, T.: Real Life, Real Users, and Real Needs: A Study and Analysis of User Queries on the Web. Information Processing & Management 36(2), 207–227 (2000)
Liddle, S., Embley, D., Scott, D., Yau, S.: Extracting Data Behind Web. In: Proceedings of the Joint Workshop on Conceptual Modeling Approaches for E-business: A Web Service Perspective (eCOMO 2002), pp. 38–49 (October 2002)
Omelayenko, B.: Learning of ontologies for the Web: the analysis of existent approaches. In: Proceedings of the International Workshop on Web Dynamics (Retrieved, 2001), http://www.dcs.bbk.ac.uk/webDyn/webDynPapers/omelayenko.pdf
Weber, N., Buitelaar, P.: Web-based Ontology Learning with ISOLDE. In: Proceedings of ISWC 2006 Workshop on Web Content Mining with Human Language Technologies (2006), http://www2.dfki.de/~paulb/
Faatz, A., Steinmetz, R.: Ontology Enrichment Evaluation. In: Motta, E., Shadbolt, N.R., Stutt, A., Gibbins, N. (eds.) EKAW 2004. LNCS (LNAI), vol. 3257, pp. 497–498. Springer, Heidelberg (2004)
Stanford Center for Biomedical Informatics Research, Protégé 3.3.1 [Computer Program] (Retrieved, 2007), http://protege.stanford.edu/download/registered.html
Raghavan, S., Garcia-Molina, H.: Crawling the Hidden Web. In: Proceedings of the 27th International Conference on Very Large Data Bases, pp. 29–138 (2001)
Liddle, S., Embley, D., Scott, D., Yau, S.: Extracting Data Behind Web Forms. In: Proceedings of the Joint Workshop on Conceptual Modeling Approaches for E-business: A Web Service Perspective (eCOMO 2002), pp. 38–49 (2002)
Ramachandran, R., Movva, S., Graves, S., Tanner, S.: Ontology-based Semantic Search Tool for Atmospheric Science. In: Proceedings of 22nd International Conference on Interactive Information Processing Systems for Meteorology, Oceanography, and Hydrology, http://ams.confex.com/ams/Annual2006/
An, Y.J.: Ontology Learning for the Semantic Deep Web, Ph.D. Dissertation in Computer Science, New Jersey Institute of Technology (January 2008)
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An, Y.J., Chun, S.A., Huang, Kc., Geller, J. (2008). Enriching Ontology for Deep Web Search. In: Bhowmick, S.S., Küng, J., Wagner, R. (eds) Database and Expert Systems Applications. DEXA 2008. Lecture Notes in Computer Science, vol 5181. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-85654-2_9
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DOI: https://doi.org/10.1007/978-3-540-85654-2_9
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