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SIGIR
2004
ACM

Belief revision for adaptive information retrieval

9 years 2 months ago
Belief revision for adaptive information retrieval
Applying Belief Revision logic to model adaptive information retrieval is appealing since it provides a rigorous theoretical foundation to model partiality and uncertainty inherent in any information retrieval (IR) processes. In particular, a retrieval context can be formalised as a belief set and the formalised context is used to disambiguate vague user queries. Belief revision logic also provides a robust computational mechanism to revise an IR system’s beliefs about the users’ changing information needs. In addition, information flow is proposed as a text mining method to automatically acquire the initial IR contexts. The advantage of a beliefbased IR system is that its IR behaviour is more predictable and explanatory. However, computational efficiency is often a concern when the belief revision formalisms are applied to large real-life applications. This paper describes our beliefbased adaptive IR system which is underpinned by an efficient belief revision mechanism. Our ini...
Raymond Y. K. Lau, Peter Bruza, Dawei Song
Added 30 Jun 2010
Updated 30 Jun 2010
Type Conference
Year 2004
Where SIGIR
Authors Raymond Y. K. Lau, Peter Bruza, Dawei Song
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