Diverse peer selection in collaborative web search

  • Authors:
  • Le-Shin Wu;Filippo Menczer

  • Affiliations:
  • Indiana University, Bloomington, IN;Indiana University, Bloomington, IN

  • Venue:
  • Proceedings of the 2009 ACM symposium on Applied Computing
  • Year:
  • 2009

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Abstract

Effective peer selection for intelligent query routing is a challenge in collaborative peer-based Web search systems, especially unstructured networks that do not have any centralized control of peer document collections. In particular, routing a query to multiple peers that provide the same results is a waste of resources. To deal with overlapping document collections we propose a diverse peer selection approach for adaptive query routing. This approach takes into account not only which neighbors are the best resource providers for a given query, but also which combinations of neighbors can provide the least redundant results. We validate the feasibility of our proposed algorithm by presenting several simulation experiments conducted with different configurations of peer network environments. Two novel evaluation measures, distributed precision and distributed recall, are also introduced to provide an effective comparison of different peer network systems. These two performance measures extend the well known IR measures of precision and recall by integrating network costs, namely bandwidth and latency. Our algorithm finds results of equivalent quality using less time and generating less traffic in the presence of varying amounts of document duplication.