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Further Experiments in Case-Based Collaborative Web Search

  • Jill Freyne
  • Barry Smyth
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4106)

Abstract

Collaborative Web Search (CWS) proposes a case-based approach to personalizing search results for the needs of a community of like-minded searchers. The search activities of users are captured as a case base of search cases, each corresponding to community search behaviour (the results selected) for a given query. When responding to a new query, CWS selects a set of similar cases and promotes their selected results within the final result-list. In this paper we describe how this case-based view can be broadened to accommodate suggestions from multiple case bases, reflecting the expertise and preferences of complementary search communities. In this way it is possible to supplement the recommendations of the host community with complementary recommendations from related communities. We describe the results of a new live-user trial that speaks to the performance benefits that are available by using multiple case bases in this way compared to the use of a single case base.

Keywords

Host Community Related Community Recommendation List Similar Query Test Query 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Jill Freyne
    • 1
  • Barry Smyth
    • 1
  1. 1.School of Computer Science and InformaticsUniversity College DublinDublin 4Ireland

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