Advertisement

Alignment-Based Preprocessing of Personal Ontologies on Semantic Social Network

  • Jason J. Jung
  • Hong-Gee Kim
  • Geun-Sik Jo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4693)

Abstract

In semantic social network, the relations between users are inferred by measuring the similarity between the corresponding personal ontologies. However, “over-enriched” personal ontologies have caused some difficulties in being discriminated from other personal ontologies. For efficiently annotating resources in their own repositories, people simply append ontology fragments retrieved from standard ontologies and from other neighbors’ personal ontologies along to social links. In this paper, we propose a preprocessing method to extract preferential concepts for comparing with social semantics. In order to prune out irrelevant concepts from personal ontologies, alignment-based concept classification process is designed by checking these two main criteria; i) redundancy (e.g., if there already exist semantically identical concepts), and ii) tendency (e.g., if there exist semantically declined concepts). Finally, we want to show an application scenario to demonstrate our contributions.

Keywords

Social Network Analysis Preferential Weight Identical Concept Simple Aggregation Preferential Concept 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Huhns, M.N., Stephens, L.M.: Agents on the web: Personal ontologies. IEEE Internet Computing 3(5), 85–87 (1999)CrossRefGoogle Scholar
  2. 2.
    Decker, S., Frank, M.R.: The networked semantic desktop. In: Bussler, C., Decker, S., Schwabe, D., Pastor, O. (eds.) Proc. of the WWW2004 Work. on Application Design, Development and Implementation Issues in the Semantic Web (2004)Google Scholar
  3. 3.
    Jung, J.J.: Collaborative web browsing based on semantic extraction of user interests with bookmarks. J. of Universal Computer Science 11(2), 213–228 (2005)Google Scholar
  4. 4.
    Jung, J.J.: Visualizing recommendation flow on social network. J. of Universal Computer Science 11(11), 1780–1791 (2005)Google Scholar
  5. 5.
    Jung, J.J.: Ontological Framework Based on Contextual Mediation for Collaborative Information Retrieval. Information Retrieval 10(1), 85–109 (2007)CrossRefGoogle Scholar
  6. 6.
    Jung, J.J., Euzenat, J.: Towards semantic social networks (to appear). In: Franconi, E., Kifer, M., May, W. (eds.) ESWC 2007. Proc. of 4th Euro. Semantic Web Conf., Springer, Heidelberg (to appear, 2007)Google Scholar
  7. 7.
    Euzenat, J., Valtchev, P.: Similarity-based ontology alignment in OWL-Lite. In: de Mántaras, R.L., Saitta, L. (eds.) ECAI’2004. Proc. of 16th Euro. Conf. on Artificial Intelligence, Valencia, Spain, August 22-27, pp. 333–337. IOS Press, Amsterdam (2004)Google Scholar
  8. 8.
    Wasserman, S., Faust, K.: Social Network Analysis. Cambridge University Press, Cambridge (1994)CrossRefzbMATHGoogle Scholar
  9. 9.
    Kleinberg, J.M.: Authoritative sources in a hyperlinked environment. J. of ACM 46(5), 604–632 (1999)MathSciNetCrossRefzbMATHGoogle Scholar
  10. 10.
    Hotho, A., Maedche, A., Staab, S.: Ontology-based text document clustering. Künstliche Intelligenz 16(4), 48–54 (2002)Google Scholar
  11. 11.
    Baumgartner, R., Henze, N., Herzog, M.: The personal publication reader: Illustrating web data extraction, personalization and reasoning for the semantic web. In: Gómez-Pérez, A., Euzenat, J. (eds.) ESWC 2005. LNCS, vol. 3532, pp. 515–530. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  12. 12.
    Haase, P., Hotho, A., Schmidt-Thieme, L., Sure, Y.: Collaborative and usage-driven evolution of personal ontologies. In: Gómez-Pérez, A., Euzenat, J. (eds.) ESWC 2005. LNCS, vol. 3532, pp. 486–499. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  13. 13.
    Mika, P.: Ontologies are us: A unified model of social networks and semantics. In: Gil, Y., Motta, E., Benjamins, V.R., Musen, M.A. (eds.) ISWC 2005. LNCS, vol. 3729, pp. 522–536. Springer, Heidelberg (2005)CrossRefGoogle Scholar
  14. 14.
    Rousset, M.C.: Small can be beautiful in the semantic web. In: McIlraith, S.A., Plexousakis, D., van Harmelen, F. (eds.) ISWC 2004. LNCS, vol. 3298, pp. 6–16. Springer, Heidelberg (2004)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Jason J. Jung
    • 1
  • Hong-Gee Kim
    • 2
  • Geun-Sik Jo
    • 1
  1. 1.Inha UniversityKorea
  2. 2.Seoul National UniversityKorea

Personalised recommendations