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Towards Building Virtual Vocabularies in the Semantic Web

  • Yunqing Wen
  • Xiang Zhang
  • Kai Shen
  • Peng Wang
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8346)

Abstract

The development of ontologies in current Semantic Web is in a distributed and loosely-coupled way. Knowledge workers build their vocabularies in accessible web ontologies in their own manner. Two extreme cases are: many highly related concepts are defined separately in a set of tiny ontology fragments; while some massive ontologies defines a large set of concepts, which semantically belong to different areas. These cases bring a barrier to ontology reuse. In this paper, we propose an approach to semantically reorganizing concepts defined in various ontologies. We transform the reorganization problem to a graph clustering problem, and the result of reorganization is a set of virtual vocabularies for reuse. Experiments on a massive ontology repository show that our approach is feasible and efficient.

Keywords

ontology virtual vocabulary semantic web 

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References

  1. 1.
    Doran, P., Tamma, V., Iannone, L.: Ontology module extraction for ontology reuse: an ontology engineering perspective. In: Proceedings of the Sixteenth ACM Conference on Conference on Information and Knowledge Management, pp. 61–70. ACM (2007)Google Scholar
  2. 2.
    Grau, B.C., Horrocks, I., Kazakov, Y., et al.: Modular reuse of ontologies: Theory and practice. Journal of Artificial Intelligence Research 31(1), 273–318 (2008)zbMATHMathSciNetGoogle Scholar
  3. 3.
    MacQueen, J.: Some methods for classification and analysis of multivariate observations. In: Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, vol. 1, pp. 281–297 (1967)Google Scholar
  4. 4.
    Zhang, H.: Extensions to the K-means algorithm for clustering large data sets with categorical Values. Data Mining and Knowledge Discovery (2), 283–304 (1998)Google Scholar
  5. 5.
    Newman, M.E.J.: Fast algorithm for detecting community structure in networks. Physical Review E 69(6), 66133 (2004)CrossRefGoogle Scholar
  6. 6.
    Newman, M.E.J., Girvan, M.: Finding and evaluating community structure in networks. Physical Review E 69(2), 026113 (2004)Google Scholar
  7. 7.
    Cheng, G., Ge, W., Qu, Y.: Falcons: searching and browsing entities on the semantic web. In: Proceedings of the 17th International Conference on World Wide Web, pp. 1101–1102. ACM (2008)Google Scholar
  8. 8.
    Schlicht, A., Stuckenschmidt, H.: Towards Structural Criteria for Ontology Modularization. In: The 1st International Workshop on Modular Ontologies (2006)Google Scholar
  9. 9.
    Seidenberg, J., Rector, A.: Web ontology segmentation: Analysis, classification and use. In: Proc. 15th Int. Conf. on World Wide Web (WWW 2006), Edinburgh, Scotland, May 23-26 (2006)Google Scholar
  10. 10.
    Simperl, E.: Reusing ontologies on the Semantic Web: A feasibility study. Data & Knowledge Engineering 68(10), 905–925 (2009)CrossRefGoogle Scholar
  11. 11.
    Surez-Figueroa, M.C.: NeOn Methodology for building ontology networks: specification, scheduling and reuse. Informatica (2010)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Yunqing Wen
    • 1
  • Xiang Zhang
    • 2
  • Kai Shen
    • 1
  • Peng Wang
    • 2
  1. 1.College of Software EngineeringSoutheast UniversityNanjingChina
  2. 2.School of Computer Science and EngineeringSoutheast UniversityNanjingChina

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