Abstract
A crucial piece of semantic web development is the creation of viable ontology matching approaches to ensure interoperability in a wide range of applications such as information integration and semantic multimedia. In this paper, a new approach for ontology matching called IROM (Information Retrieval-based Ontology Matching) is presented. This approach derives the different components of an information retrieval (IR) framework based on the information provided by the input ontologies and supported by ontology similarity measures. Subsequently, a retrieval algorithm is applied to determine the correspondences between the matched ontologies. IROM was tested with ontology pairs taken from two resources for reference ontologies, OAEI and FOAM. The evaluation shows that IROM is competitive with top-ranked matchers on the benchmark test at OAEI campaign of 2009.
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References
Baeza-Yates, R., Ribeiro-Neto, B.: Modern Information Retrieval, 1st edn. Addison Wesley, Reading (1999)
Budanitsky, A., Hirst, G.: Evaluating wordnet-based measures of lexical semantic relatedness. Computational Linguistics 32(1), 13–47 (2006)
Ehrig, M.: Ontology alignment: bridging the semantic gap. Springer-Verlag New York Inc., Heidelberg (2007)
Euzenat, J.: An API for ontology alignment. LNCS, pp. 698–712 (2004)
Euzenat, J., Shvaiko, P.: Ontology Matching. Springer-Verlag New York Inc., New York (2007)
Jean-Mary, Y., Shironoshita, E., Kabuka, M.: Ontology matching with semantic verification. Web Semantics: Science, Services and Agents on the World Wide Web 7(3), 235–251 (2009)
Jiang, J.J., Conrath, D.W.: Semantic similarity based on corpus statistics and lexical taxonomy. In: International Conference Research on Computational Linguistics (ROCLING X), p. 9008+ (September 1997)
Kontostathis, A.: Essential dimensions of latent semantic indexing (lsi). In: Hawaii International Conference on System Sciences, vol. 40, Citeseer (2007)
Landauer: Handbook of Latent Semantic Analysis. Lawrence Erlbaum Associates, Mahwah (2007)
Letsche, T.A., Berry, M.W.: Large-scale information retrieval with latent semantic indexing (1997)
Levenshtein, V.: Binary Codes Capable of Correcting Deletions, Insertions and Reversals. Soviet Physics Doklady 10, 707 (1966)
Mao, M., Peng, Y., Spring, M.: An adaptive ontology mapping approach with neural network based constraint satisfaction. Web Semantics: Science, Services and Agents on the World Wide Web (2009)
Nagy, M., Vargas-Vera, M., Motta, E.: DSSim–managing uncertainty on the semantic web. In: Proceedings of the International Workshop on Ontology Matching, Citeseer (2007)
Resnik, P.: Using information content to evaluate semantic similarity in a taxonomy. In: International Joint Conference on Artificial Intelligence, vol. 14, pp. 448–453 (1995)
Seddiqui, M., Aono, M.: Anchor-Flood: Results for OAEI-2009. In: Proceedings of Ontology Matching Workshop of the 8th International Semantic Web Conference, Chantilly, VA, USA (2009)
Styltsvig, H.B.: Ontology-based Information Retrieval. PhD thesis, Roskilde University, Denmark (2006)
Tang, J., Li, J., Liang, B., Huang, X., Li, Y., Wang, K.: Using Bayesian decision for ontology mapping. Web Semantics: Science, Services and Agents on the World Wide Web 4(4), 243–262 (2006)
Wang, P., Xu, B.: LILY: the results for the ontology alignment contest OAEI 2007. In: Proceedings of ISWC 2007 Ontology Matching Workshop, Busan, Korea, Citeseer (2007)
Wu, Z., Palmer, M.: Verbs semantics and lexical selection. In: Proceedings of the 32nd Annual Meeting on Association for Computational Linguistics, pp. 133–138. Association for Computational Linguistics, Morristown (1994)
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Mousselly-Sergieh, H., Unland, R. (2011). IROM: Information Retrieval-Based Ontology Matching. In: Declerck, T., Granitzer, M., Grzegorzek, M., Romanelli, M., Rüger, S., Sintek, M. (eds) Semantic Multimedia. SAMT 2010. Lecture Notes in Computer Science, vol 6725. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-23017-2_9
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DOI: https://doi.org/10.1007/978-3-642-23017-2_9
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