Searching dynamic communities with personal indexes

  • Authors:

  • Alexander Löser;Christoph Tempich;Bastian Quilitz;Wolf-Tilo Balke;Steffen Staab;Wolfgang Nejdl

  • Affiliations:

  • CIS, University of Technology Berlin, Berlin, Germany;AIFB, University of Karlsruhe, Karlsruhe, Germany;CIS, University of Technology Berlin, Berlin, Germany;L3S, University of Hannover, Hannover, Germany;ISWeb, University of Koblenz Landau, Koblenz, Germany;L3S, University of Hannover, Hannover, Germany

  • Venue:
  • ISWC'05 Proceedings of the 4th international conference on The Semantic Web
  • Year:
  • 2005

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Abstract

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.