Abstract
Ontology matching is a crucial task to enable interoperation between Web applications using different but related ontologies. Today, most of the ontology matching techniques are targeted to find 1:1 mappings. However, block mappings are in fact more pervasive. In this paper, we discuss the block matching problem and suggest that both the mapping quality and the partitioning quality should be considered in block matching. We propose a novel partitioning-based approach to address the block matching issue. It considers both linguistic and structural characteristics of domain entities based on virtual documents, and uses a hierarchical bisection algorithm for partitioning. We set up two kinds of metrics to evaluate of the quality of block matching. The experimental results demonstrate that our approach is feasible.
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Castano, S., De Antonellis, V., De Capitani Di Vimercati, S.: Global viewing of heterogeneous data sources. IEEE Transactions on Knowledge and Data Engineering 13(2), 277–297 (2001)
Cheng, D., Kannan, R., Vempala, S., Wang, G.: A divide-and-merge methodology for clustering. In: Proceedings of the 24th ACM Symposium on Principles of Database Systems (PODS 2005), pp. 196–205 (2005)
Cuenca Grau, B., Parsia, B., Sirin, E.: Combining OWL ontologies using ε-connections. Journal of Web Semantics 4(1) (2005)
Dhamankar, R., Lee, Y., Doan, A.H., Halevy, A., Domingos, P.: iMAP: Discovering complex semantic matches between database schemas. In: Proceedings of the 23th ACM International Conference on Management of Data (SIGMOD 2004), pp. 383–394 (2004)
Ding, C.H.Q., He, X., Zha, H., Gu, M., Simon, H.D.: A min-max cut algorithm for graph partitioning and data clustering. In: Proceedings of the 2001 IEEE International Conference on Data Mining (ICDM 2001), pp. 107–114 (2001)
Doan, A., Madhavan, J., Dhamankar, R., Domingos, P., Halevy, A.Y.: Learning to match ontologies on the semantic web. VLDB Journal 12(4), 303–319 (2003)
Ehrig, M., Staab, S.: QOM - quick ontology mapping. In: McIlraith, S.A., Plexousakis, D., van Harmelen, F. (eds.) ISWC 2004. LNCS, vol. 3298, pp. 683–697. Springer, Heidelberg (2004)
Euzenat, J., Valtchev, P.: Similarity-based ontology alignment in OWL-Lite. In: Proceedings of the 16th European Conference on Artificial Intelligence (ECAI 2004), pp. 333–337 (2004)
Fiedler, M.: A property of eigenvectors of nonnegative symmetric matrices and its application to graph theory. Czechoslovak Mathematical Journal 25, 619–633 (1975)
Giunchiglia, F., Shvaiko, P., Yatskevich, M.: S-Match: An algorithm and an implementation of semantic matching. In: Bussler, C.J., Davies, J., Fensel, D., Studer, R. (eds.) ESWS 2004. LNCS, vol. 3053, pp. 61–75. Springer, Heidelberg (2004)
Hu, W., Zhao, Y.Y., Qu, Y.Z.: Partition-based block matching of large class hierarchies. In: Mizoguchi, R., Shi, Z.-Z., Giunchiglia, F. (eds.) ASWC 2006. LNCS, vol. 4185, pp. 72–83. Springer, Heidelberg (2006)
Klyne, G., Carroll, J.J. (eds.): Resource description framework (RDF): Concepts and abstract syntax. W3C Recommendation (February 10, 2004), latest version is available at: http://www.w3.org/TR/rdf-concepts/
Kotis, K., Vouros, G.A., Stergiou, K.: Towards automatic merging of domain ontologies: The HCONE-merge approach. Journal of Web Semantics 4(1) (2005)
Noy, N.F., Musen, M.A.: The PROMPT suite: Interactive tools for ontology merging and mapping. International Journal of Human-Computer Studies 59, 983–1024 (2003)
Noy, N.F., Musen, M.A.: Specifying ontology views by traversal. In: McIlraith, S.A., Plexousakis, D., van Harmelen, F. (eds.) ISWC 2004. LNCS, vol. 3298, pp. 713–725. Springer, Heidelberg (2004)
Parlett, B.N.: The symmetric eigenvalue problem. SIAM, Philadelphia (1998)
Raghavan, V.V., Wong, S.K.M.: A critical analysis of vector space model for information retrieval. Journal of the American Society for Information Science 37(5), 279–287 (1986)
Rahm, E., Bernstein, P.: A survey of approaches to automatic schema matching. VLDB Journal 10, 334–350 (2001)
Patel-Schneider, P.F., Hayes, P., Horrocks, I. (eds.): OWL web ontology language semantics and abstract syntax. W3C Recommendation (February 10, 2004), latest version is available at: http://www.w3.org/TR/owl-semantics/
Qu, Y.Z., Hu, W., Cheng, G.: Constructing virtual documents for ontology matching. In: Proceedings of the 15th International World Wide Web Conference (WWW 2006), pp. 23–31 (2006)
Salton, G., McGill, M.H.: Introduction to modern information retrieval. McGraw-Hill, New York (1983)
Seidenberg, J., Rector, A.: Web ontology segmentation: analysis, classification and use. In: Proceedings of the 15th International World Wide Web Conference (WWW 2006), pp. 13–22 (2006)
Stoilos, G., Stamou, G., Kollias, S.: A string metric for ontology alignment. In: Gil, Y., Motta, E., Benjamins, V.R., Musen, M.A. (eds.) ISWC 2005. LNCS, vol. 3729, pp. 623–637. Springer, Heidelberg (2005)
Stuckenschmidt, H., Klein, M.: Structure-based partitioning of large concept hierarchies. In: McIlraith, S.A., Plexousakis, D., van Harmelen, F. (eds.) ISWC 2004. LNCS, vol. 3298, pp. 289–303. Springer, Heidelberg (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Hu, W., Qu, Y. (2006). Block Matching for Ontologies. In: Cruz, I., et al. The Semantic Web - ISWC 2006. ISWC 2006. Lecture Notes in Computer Science, vol 4273. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11926078_22
Download citation
DOI: https://doi.org/10.1007/11926078_22
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-49029-6
Online ISBN: 978-3-540-49055-5
eBook Packages: Computer ScienceComputer Science (R0)