Searching Dynamic Communities with Personal Indexes

  • Alexander Löser
  • Christoph Tempich
  • Bastian Quilitz
  • Wolf-Tilo Balke
  • Steffen Staab
  • Wolfgang Nejdl
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3729)


Often the challenge of finding relevant information is reduced to find the ‘right’ people who will answer our question. In this paper we present innovative algorithms called INGA (Interest-based Node Grouping Algorithms) which integrate personal routing indices into semantic query processing to boost performance. Similar to social networks peers in INGA cooperate to efficiently route queries for documents along adaptive shortcut-based overlays using only local, but semantically well chosen information. We propose active and passive shortcut creation strategies for index building and a novel algorithm to select the most promising content providers depending on each peer index with respect to the individual query. We quantify the benefit of our indexing strategy by extensive performance experiments in the SWAP simulation infrastructure. While obtaining high recall values compared to other state-of-the-art algorithms, we show that INGA improves recall and reduces the number of messages significantly.


  1. 1.
    Aberer, K., Cudre-Mauroux, P., Hauswirth, M., van Pelt, T.: GridVine: Building Internet- Scale Semantic Overlay Networks. In: McIlraith, S.A., Plexousakis, D., van Harmelen, F. (eds.) ISWC 2004. LNCS, vol. 3298, pp. 107–121. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  2. 2.
    Aho, A.V., Denning, P.J., Ullman, J.D.: Principles of optimal page replacement. J. ACM 18(1), 80–93 (1971)MATHCrossRefMathSciNetGoogle Scholar
  3. 3.
    Allan, J.: Incremental relevance feedback for information filtering. In: SIGIR 1996: Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval, pp. 270–278. ACM Press, New York (1996)CrossRefGoogle Scholar
  4. 4.
    Androutsellis-Theotokis, S., Spinellis, D.: A survey of peer-to-peer content distribution technologies. ACM Comput. Surv. 36(4), 335–371 (2004)CrossRefGoogle Scholar
  5. 5.
    Balke, W.-T., Nejdl, W., Siberski, W., Thaden, U.: Progressive distributed top-k retrieval in peer-to-peer networks. In: 21st International Conference on Data Engineering (ICDE), Tokyo, Japan (2005)Google Scholar
  6. 6.
    Condie, T., Kamvar, S., Garcia-Molina, H.: Adaptive Peer-to-Peer Topologies. In: Int. Conf. on Peer-to-Peer Computing (P2P), Zurich, Switzerland (2004)Google Scholar
  7. 7.
    Cooper, B.: Guiding queries to information sources with InfoBeacons. In: ACM/IFIP/USENIX 5th International Middleware Conference, Toronto (2004)Google Scholar
  8. 8.
    Crespo, A., Garcia-Molina, H.: Routing indices for peer-to-peer systems. In: International Conference on Distributed Computing Systems (July 2002)Google Scholar
  9. 9.
    Gravano, L., Garc´ýa-Molina, H.: Generalizing GlOSS to vector-space databases and broker hierarchies. In: International Conference on Very Large Databases, VLDB, pp. 78–89 (1995)Google Scholar
  10. 10.
    Haase, P., et al.: Bibster - a semantics-based bibliographic peer-to-peer system. In: McIlraith, S.A., Plexousakis, D., van Harmelen, F. (eds.) ISWC 2004. LNCS, vol. 3298, pp. 122–136. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  11. 11.
    Keleher, P.J., Bhattacharjee, B., Silaghi, B.D.: Are virtualized overlay networks too much of a good thing. In: IPTPS 2001: Revised Papers from the First International Workshop on Peer-to-Peer Systems, pp. 225–231. Springer, Heidelberg (2002)Google Scholar
  12. 12.
    Kleinberg, J.: Navigation in a small world. Nature 406 (2000)Google Scholar
  13. 13.
    Li, Y., Bandar, Z., McLean, D.: An Approach for messuring semantic similarity between words using semantic multiple information sources. IEEE Transactions on Knowledge and Data Engineering 15 (2003)Google Scholar
  14. 14.
    Loo, B., Hellerstein, J., Huebsch, R., Shenker, S., Stoica, I.: Enhancing p2p file-sharing with an internet-scale query processor. In: Proc. of Int. Conf. on Very Large Databases (VLDB), Toronto (2004)Google Scholar
  15. 15.
    Milgram, S.: The small world problem. Psychology Today 67(1) (1967)Google Scholar
  16. 16.
    Nejdl, W., Wolpers, M., Siberski, W., Löser, A., Bruckhorst, I., Schlosser, M., Schmitz, C.: Super-Peer-Based Routing and Clustering Strategies for RDF-Based Peer-To-Peer Networks. In: 12th International World Wide Web Conference, Budapest, Hungary (May 2003)Google Scholar
  17. 17.
    Saroiu, S., Gummadi, P.K., Gribble, S.D.: A measurement study of peer-to-peer file sharing systems. Multimedia Systems 9(2) (2003)Google Scholar
  18. 18.
    Sripanidkulchai, K., Maggs, B., Zhang, H.: Efficient Content Location Using Interest Based Locality in Peer-to-Peer System. In: Infocom. IEEE, Los Alamitos (2003)Google Scholar
  19. 19.
    Tempich, C., Staab, S., Wranik, A.: REMINDIN:Semantic Query Routing in Peer-to-Peer Networks based on Social Metaphers. In: Proceedings of the 13th WWW Conference New York. ACM, New York (2004)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Alexander Löser
    • 1
  • Christoph Tempich
    • 3
  • Bastian Quilitz
    • 1
  • Wolf-Tilo Balke
    • 2
  • Steffen Staab
    • 4
  • Wolfgang Nejdl
    • 2
  1. 1.CISUniversity of Technology BerlinBerlinGermany
  2. 2.L3SUniversity of HannoverHannoverGermany
  3. 3.AIFBUniversity of KarlsruheKarlsruheGermany
  4. 4.ISWebUniversity of Koblenz LandauKoblenzGermany

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