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Information Retrieval in Trust-Enhanced Document Networks

  • Klaus Stein
  • Claudia Hess
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4289)

Abstract

To fight the problem of information overload in huge information sources like large document repositories, e. g. citeseer, or internet websites you need a selection criterion: some kind of ranking is required. Ranking methods like PageRank analyze the structure of the document reference network. However, these rankings do not distinguish different reference semantics. We enhance these rankings by incorporating information of a second layer: the author trust network to improve ranking quality and to enable personalized selections.

Keywords

Information Retrieval Visibility Function Edge Weight Trust Information Trust Network 
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.

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References

  1. 1.
    Page, L., Brin, S., Motwani, R., Winograd, T.: The pagerank citation ranking: Bringing order to the web. Technical report, Stanford Digital Library Technologies Project (1998)Google Scholar
  2. 2.
    Watts, D.J.: Six Degrees: The Science of a Connected Age. W. W. Norton & Company, Inc. (2003)Google Scholar
  3. 3.
    Barabási, A.L.: Linked: How Everything Is Connected to Everything Else and What It Means for Business, Science, and Everyday Life. In: PLUME (2003)Google Scholar
  4. 4.
    Menczer, F.: Growing and navigating the small world web by local content. In: Proceedings of the National Academy of Sciences of the United States of America, vol. 99, pp. 14014–14019 (2002)Google Scholar
  5. 5.
    Newman, M.E.J.: The structure and function of complex networks. SIAM Review 45, 167–256 (2003)MATHCrossRefMathSciNetGoogle Scholar
  6. 6.
    Pinski, G., Narin, F.: Citation influence for journal aggregates of scientific publications: Theory, with application to the literature of physics. Information Processing & Management 12, 297–312 (1976)CrossRefGoogle Scholar
  7. 7.
    Brin, S., Page, L.: The anatomy of a large-scale hypertextual Web search engine. Computer Networks and ISDN Systems 30, 107–117 (1998)CrossRefGoogle Scholar
  8. 8.
    Malsch, T., Schlieder, C., Kiefer, P., Lübcke, M., Perschke, R., Schmitt, M., Stein, K.: Communication between process and structure: Modelling and simulating message-reference-networks with COM/TE. JASSS (accepted, 2005)Google Scholar
  9. 9.
    Golbeck, J., Parsia, B., Hendler, J.: Trust networks on the semantic web. In: Proceedings of Cooperative Intelligent Agents, Helsinki, Finland (2003)Google Scholar
  10. 10.
    Ziegler, C.N., Lausen, G.: Spreading activation models for trust propagation. In: Proceedings of the IEEE International Conference on e-Technology, e-Commerce, and e-Service, Taipei, Taiwan. IEEE Computer Society Press, Los Alamitos (2004)Google Scholar
  11. 11.
    Guha, R., Kumar, R., Raghavan, P., Tomkins, A.: Propagation of trust and distrust. In: WWW 2004: Proceedings of the 13th international conference on World Wide Web, pp. 403–412. ACM Press, New York (2004)CrossRefGoogle Scholar
  12. 12.
    Matsuo, Y., Tomobe, H., Hasida, K., Ishizuk, M.: Finding social network for trust calculation. In: Proceedings of the 16th European Conference on Artificial Intelligence (ECAI 2004), pp. 510–514 (2004)Google Scholar
  13. 13.
    Guha, R.: Open rating systems. Technical report, Stanford Knowledge Systems Laboratory, Stanford, CA, USA (2003)Google Scholar
  14. 14.
    Montaner, M., López, B., Lluís de la Rosa, J.: Opinion-based filtering through trust. In: Klusch, M., Ossowski, S., Shehory, O. (eds.) CIA 2002. LNCS (LNAI), vol. 2446, pp. 188–196. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  15. 15.
    Kinateder, M., Rothermel, K.: Architecture and algorithms for a distributed reputation system. In: Nixon, P., Terzis, S. (eds.) iTrust 2003. LNCS, vol. 2692, pp. 1–16. Springer, Heidelberg (2003)CrossRefGoogle Scholar
  16. 16.
    Hess, C., Stein, K., Schlieder, C.: Trust-enhanced visibility for personalized document recommendations. In: Proceedings of the 21st Annual ACM Symposium on Applied Computing (2006)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Klaus Stein
    • 1
  • Claudia Hess
    • 1
  1. 1.Laboratory for Semantic Information TechnologyBamberg University 

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