Advertisement

Peer Selection in Peer-to-Peer Networks with Semantic Topologies

  • Peter Haase
  • Ronny Siebes
  • Frank van Harmelen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3226)

Abstract

Peer-to-Peer systems have proven to be an effective way of sharing data. Modern protocols are able to efficiently route a message to a given peer. However, determining the destination peer in the first place is not always trivial. We propose a model in which peers advertise their expertise in the Peer-to-Peer network. The knowledge about the expertise of other peers forms a semantic topology. Based on the semantic similarity between the subject of a query and the expertise of other peers, a peer can select appropriate peers to forward queries to, instead of broadcasting the query or sending it to a random set of peers. To calculate our semantic similarity measure we make the simplifying assumption that the peers share the same ontology. We evaluate the model in a bibliographic scenario, where peers share bibliographic descriptions of publications among each other. In simulation experiments we show how expertise based peer selection improves the performance of a Peer-to-Peer system with respect to precision, recall and the number of messages.

Keywords

Semantic Similarity Latent Semantic Indexing Expertise Model Topic Distribution Semantic Similarity Measure 
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

  1. 1.
    Ahlborn, B., Nejdl, W., Siberski, W.: OAI-P2P: A peer-to-peer network for open archives. In: 2002 International Conference on Parallel Processing Workshops, ICPPW 2002 (2002)Google Scholar
  2. 2.
    Berners-Lee, T., Hendler, J., Lassila, O.: The semantic web. Scientific American (2001)Google Scholar
  3. 3.
    Berry, M.W., Drmac, Z., Jessup, E.R.: Matrices, vector spaces, and information retrieval. SIAM Review, 335–362 (1999)Google Scholar
  4. 4.
    Bonifacio, M., Cuel, R., Mameli, G., Nori, M.: A peer-to-peer architecture for distributed knowledge management. In: Proceedings of the 3rd International Symposium on Multi-Agent Systems, Large Complex Systems, and E-Businesses MALCEB (2002)Google Scholar
  5. 5.
    Broekstra, J., Ehrig, M., Haase, P., van Harmelen, F., Menken, M., Mika, P., Schnizler, B., Siebes, R.: Bibster - a semantics-based bibliographic peer-to-peer system. In: Proceedings of the WWW 2004 Workshop on Semantics in Peer-to-Peer and Grid Computing, New York (2004)Google Scholar
  6. 6.
    Broekstra, J., Kampman, A.: SeRQL: An RDF Query and Transformation Language. In: Submitted to the International Semantic Web Conference, ISWC (2004), http://www.openrdf.org/doc/SeRQLmanual.html
  7. 7.
    Ehrig, M., Schmitz, C., Staab, S., Tane, J., Tempich, C.: Towards evaluation of peer-to-peer-based distributed knowledge management systems. In: Proceedings of the AAAI Spring Symposium Agent-Mediated Knowledge Management, AMKM 2003 (2003)Google Scholar
  8. 8.
    Kautz, B.S.H., Shah, M.: Referralweb: Combining social networks and collaborative filtering.Communications of the ACM (March 1997)Google Scholar
  9. 9.
    Li, L., Horrocks, I.: A software framework for matchmaking based on semantic web technology. In: Proceedings of the Twelfth InternationalWorldWideWeb Conference (WWW 2003), pp. 331–339. ACM Press, New York (2003)Google Scholar
  10. 10.
    Li, Y., Bandar, Z.A., McLean, D.: An approach for measuring semantic similarity between words using multiple information sources. Transactions on Knowledge and Data Engineering 15(4), 871–882 (2003)CrossRefGoogle Scholar
  11. 11.
    Löser, A., Wolpers, M., Siberski, W., Nejdl, W.: Efficient data store discovery in a scientific P2P network. In: Ashish, N., Goble, C. (eds.) Proceedings of the WS on Semantic Web Technologies for Searching and Retrieving Scientific Data, CEUR WS 83 (2003) ,Colocated with the 2. ISWC 2003Google Scholar
  12. 12.
    Nejdl, W., Wolpers, M., Siberski, W., Schmitz, C., Schlosser, M., Brunkhorst, I., Löser, A.: Super-peer-based routing and clustering strategies for rdf-based peer-to-peer networks. In: Proceedings of the 12th International World Wide Web Conference, Budapest, Hungary (May 2003)Google Scholar
  13. 13.
    Rada, R., Mili, H., Bicknell, E., Blettner, M.: Development and application of a metric on semantic nets. IEEE Transactions on Systems, Man, and Cybernetics 19(1), 17–30 (1989)CrossRefGoogle Scholar
  14. 14.
    Ratnasamy, S., Francis, P., Handley, M., Karp, R., Shenker, S.: A scalable content-addressable network. In: Proceedings of ACM SIGCOMM 2001 (2001)Google Scholar
  15. 15.
    Stoica, I., Morris, R., Karger, D., Frans Kaashoek, M., Balakrishnan, H.: Chord: A scalable peer-to-peer lookup service for Internet applications. In: Proceedings of the ACM SIGCOMM 2001 (2001)Google Scholar
  16. 16.
    Sycara, K., Decker, K., Williamson, M.: Middle-agents for the internet. In: Proceedings of IJCAI 1997 (January 1997)Google Scholar
  17. 17.
    Tang, C., Xu, Z., Dwarkadas, S.: Peer-to-peer information retrieval using self-organizing semantic overlay networks. In: Proceedings of the ACM SIGCOMM Conference, Karlsruhe, Germany (August. 2003)Google Scholar
  18. 18.
    Tempich, C., Staab, S., Wranik, A.: REMINDIN’: Semantic query routing in peer-to-peer networks based on social metaphors. In: Proceedings of the 13th Int.WorldWide Web Conference, WWW 2004 (2004)Google Scholar
  19. 19.
    Yolum, P., Singh, M.P.: Dynamic communities in referral networks. Web Intelligence and Agent Systems 1(2), 105–116 (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Peter Haase
    • 1
  • Ronny Siebes
    • 2
  • Frank van Harmelen
    • 2
  1. 1.Institute AIFBUniversity of KarlsruheKarlsruheGermany
  2. 2.Vrije Universiteit AmsterdamThe Netherlands

Personalised recommendations