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Artificial Intelligence Review

, Volume 21, Issue 3–4, pp 229–252 | Cite as

Further Experiments on Collaborative Ranking in Community-Based Web Search

  • Jill Freyne
  • Barry Smyth
  • Maurice Coyle
  • Evelyn Balfe
  • Peter Briggs
Article

Abstract

As the search engine arms-race continues, search engines are constantly looking for ways to improve the manner in which they respond to user queries. Given the vagueness of Web search queries, recent research has focused on ways to introduce context into the search process as a means of clarifying vague, under-specified or ambiguous query terms. In this paper we describe a novel approach to using context in Web search that seeks to personalize the results of a generic search engine for the needs of a specialist community of users. In particular we describe two separate evaluations in detail that demonstrate how the collaborative search method has the potential to deliver significant search performance benefits to end-users while avoiding many of the privacy and security concerns that are commonly associated with related personalization research.

context personalization relevance web search 

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Copyright information

© Kluwer Academic Publishers 2004

Authors and Affiliations

  • Jill Freyne
  • Barry Smyth
  • Maurice Coyle
  • Evelyn Balfe
  • Peter Briggs

There are no affiliations available

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