Analysis Of Concept Similarity Methods Applied To An Lsh Function

In literature, there are several methods to measure similarity between concepts in structures like simple ontologies, concept hierarchies, taxonomies, etc. These measures are used to search for similar concepts. In the Semantic Web, such structures are commonly used to classify data which opens the possibility of reasoning upon them and helps in conceptual searches. Besides that, the Locality Sensitive Hash (LSH) functions are used to store similar data close to each other in an index space. Each family of LSH functions is tied to a specific similarity function. In this paper we propose a method for combining the idea of conceptual similarity with LSH functions. This method permits the data classified as similar concepts be indexed close to each other respecting some metric. The main idea is to facilitate the conceptual searching for data semantically classified. This paper evaluates several methods of measuring the similarity between concepts in a simple ontology and discusses how they can be applied to an LSH function. © 2011 IEEE.547555IEEE,IEEE Computer SocietyLi, Y., Bandar, Z., Mclean, D., An approach for measuring semantic similarity between words using multiple information sources (2003) Knowledge and Data Engineering, 15 (4), pp. 871-882. , IEEE Transactions on july-augRada, R., Mili, H., Bicknell, E., Blettner, M., Development and application of a metric on semantic nets (1989) Systems, Man and Cybernetics, 19 (1), pp. 17-30. , IEEE Transactions on jan/febResnik, P., Semantic Similarity in a Taxonomy: An Information-Based Measure and its Application to Problems of Ambiguity in Natural Language (1999) Journal of Artificial Intelligence Research, 11, pp. 95-130Berners-Lee, T., Hendler, J., Lassila, O., The semantic web: A new form of web content that is meaningful to computers will unleash a revolution of new possibilities (2001) Scientific American, , MayBouquet, P., Kuper, G.M., Scoz, M., Zanobini, S., Asking and answering semantic queries (2004) Workshop on Meaning Coordination and Negotiation Workshop (MCN-04) in Conjunction with the 3rd International Semantic Web Conference (ISWC-04), , Hiroshima, Japan, NovemberIndyk, P., Motwani, R., Approximate nearest neighbors: Towards removing the curse of dimensionality (1998) STOC '98: Proceedings of the Thirtieth Annual ACM Symposium on Theory of Computing. New York, pp. 604-613. , NY, USA: ACMRatinov, L., Roth, D., Srikumar, V., Conceptual search and text categorization (2008) Technical Report UIUCDCS-R-2008-2932, UIUC, CS Dept.Dick, J.P., Representation of legal text for conceptual retrieval (1991) Proceedings of the 3rd International Conference on Artificial Intelligence and Law, Ser. ICAIL '91, pp. 244-253. , New York, NY, USA: ACM [Online]. Available: http://doi.acm.org/10.1145/ 112646.112676Cordí, V., Lombardi, P., Martelli, M., Mascardi, V., An ontology-based similarity between sets of concepts (2005) Simulazione e Analisi Formale Di Sistemi Complessi - WOA 2005, pp. 16-21Leacock, C., Chodorow, M., Combining local context and wordnet similarity for word sense identification (1998) Fellbaum MIT PressWu, Z., Palmer, M., Verb semantics and lexical selection (1994) Proceedings of the 32nd Annual Meeting of the Association for Computational Linguistics, pp. 133-138Charikar, M.S., Similarity estimation techniques from rounding algorithms (2002) Conference Proceedings of the Annual ACM Symposium on Theory of Computing, pp. 380-388Olszak, A., Hycube: A dht routing system based on a hierarchical hypercube geometry (2010) Parallel Processing and Applied Mathematics, Ser. Lecture Notes in Computer Science, 6068, pp. 260-269. , R. Wyrzykowski, J. Dongarra, K. Karczewski, and J. Wasniewski, Eds. Springer Berlin / HeidelbergJoung, Y.-J., Fang, C.-T., Yang, L.-W., Keyword search in dht-based peer-to-peer networks (2005) Distributed Computing Systems, 2005, pp. 339-348. , ICDCS 2005. Proceedings. 25th IEEE International Conference onRostami, H., Habibi, J., Livani, E., Semantic routing of search queries in p2p networks (2008) J. Parallel Distrib. Comput., 68 (12), pp. 1590-1602Scholosser, M., Sintek, M., Decker, S., Nejdl, W., HyperCuP - Hypercubes, ontologies and efficient search on P2P networks (2002) International Workshop on Agents and Peer-to-peer ComputingZhu, Y., (2005) Enhancing Search Performance in Peer-to-peer Networks, , Ph.D. dissertation, Computer Science and Engineering, University of CincinnatiHaghani, P., Michel, S., Aberer, K., Distributed similarity search in high dimensions using locality sensitive hashing (2009) Proceedings of the 12th International Conference on Extending Database Technology (EDBT'09), , http://www.math.spbu.ru/edbticdt/, [Online]De Paula, L.B., Villaça, R.S., Magalhães, M.F., A locality sensitive hashing approach for conceptual classification (2010) 4th International Conference on Semantic Computing - ICSC201