Abstract
This paper is concerned with the problem of semantic search. By semantic search, we mean searching for instances from knowledge base. Given a query, we are to retrieve ‘relevant’ instances, including those that contain the query keywords and those that do not contain the keywords. This is contrast to the traditional approaches of generating a ranked list of documents that contain the keywords. Specifically, we first employ keyword based search method to retrieve instances for a query; then a proposed method of semantic feedback is performed to refine the search results; and then we conduct re-retrieval by making use of relations and instance similarities. To make the search more effective, we use weighted ontology as the underlying data model in which importances are assigned to different concepts and relations. As far as we know, exploiting instance similarities in search on weighted ontology has not been investigated previously. For the task of instance similarity calculation, we exploit both concept hierarchy and properties. We applied our methods to a software domain. Empirical evaluation indicates that the proposed methods can improve the search performance significantly.
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References
Berners-Lee, T., Hendler, J., Lassila, O.: The Semantic Web. Scientific American 284(5), 34–43 (2001)
Guha, R., McCool, R., Miller, E.: Semantic Search. In: Proceedings of the Twelfth International World Wide Web Conference (WWW 2003), Budapest, Hungary, pp. 700–709 (2003)
Anyanwu, K., Sheth, A.: The ρ Operator: Discovering and Ranking Associations on the Semantic Web. SIGMOD Record 31, 42–47 (2002)
Rocha, C., Schwabe, D., Poggi, M.: A Hybrid Approach for Searching in the Semantic Web. In: Proceedings of the Thirteenth International World Wide Web Conference (2004)
Stojanovic, N., Struder, R., Stojanovic, L.: An Approach for the Ranking of Query Results in the Semantic Web. In: Fensel, D., Sycara, K., Mylopoulos, J. (eds.) ISWC 2003. LNCS, vol. 2870, pp. 500–516. Springer, Heidelberg (2003)
Gruber, T.R.: A Translation Approach to Portable Ontology Specifications. Knowledge Acquisition 5, 199–220 (1993)
Liang, B.Y., Tang, J., Wu, G., Zhang, P., Zhang, K., et al.: SWARMS: A Tool for Exploring Domain Knowledge on Semantic Web. In: AAAI 2005 workshop: Contexts and Ontologies: Theory, Practice and Applications (2005)
Dean, M., Schreiber, G. (eds.): OWL Web Ontology Language Reference. W3C Recommendation (2004), http://www.w3.org/TR/owl-ref/
Davies, J., Weeks, R., Krohn, U.: QuizRDF: Search Technology for the Semantic Web. In: WWW 2002 workshop on RDF & Semantic Web Applications, Hawaii, USA (2002)
Froogle, http://froogle.google.com
Sheth, A., Bertram, C., Avant, D., Hammond, B., Kochut, K., Warke, Y.: Managing Semantic Content for the Web. IEEE Internet Computing 6(4), 80–87 (2002)
Ganesan, P., Garcia-Molina, H., Widom, J.: Exploiting Hierarchical Domain Structure to Compute Similarity. ACM Trans. Inf. Syst. 21(1), 64–93 (2003)
Ricardo, B.Y., Berthier, R.N.: Modern Information Retrieval. Pearson Education Limited, London (1999)
van Rijsbergen, C.J.: Information Retrieval, 2nd edn. Butterworths, London (1979)
Strehl, A., Ghosh, J., Mooney, R.: Impact of Similarity Measures on Web-page Clustering. In: Proceedings of the AAAI Workshop on AI for Web Search (2000)
Salton, G., Buckley, C.: Term-weighting Approaches in Automatic Text Retrieval. Inf. Process. Manage 24(5), 513–523 (1988)
Singhal, A.: Modern Information Retrieval: A Brief Overview. Bulletin of the IEEE Computer Society Technical Committee on Data Engineering 24(4), 35–43 (2001)
Chen, H., Ng, T.: An Algorithmic Approach to Concept Exploration in a Large Knowledge Network (Automatic Thesaurus Consultation); Symbolic Branch-and-Bound vs. Connectionist Hopfield Net Activation. Journal of the American Society for Information Science 46(5), 348–369 (1995)
Cohen, P., Kjeldsen, R.: Information Retrieval by Constrained Spreading Activation on Semantic Networks. Information Processing and Management 23(4), 255–268 (1987)
O’Hara, K., Alani, H., Shadbolt, N.: Identifying Communities of Practices: Analyzing Ontologies as Networks to Support Community Recognition. In: IFIP-WCC, Montreal (2002)
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Zhang, K., Tang, J., Hong, M., Li, J., Wei, W. (2006). Weighted Ontology-Based Search Exploiting Semantic Similarity. In: Zhou, X., Li, J., Shen, H.T., Kitsuregawa, M., Zhang, Y. (eds) Frontiers of WWW Research and Development - APWeb 2006. APWeb 2006. Lecture Notes in Computer Science, vol 3841. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11610113_44
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DOI: https://doi.org/10.1007/11610113_44
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