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2005
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Comparing relevance feedback algorithms for web search

9 years 11 months ago
Comparing relevance feedback algorithms for web search
We evaluate three different relevance feedback (RF) algorithms, Rocchio, Robertson/Sparck-Jones (RSJ) and Bayesian, in the context of Web search. We use a target-testing experimental procedure whereby a user must locate a specific document. For user relevance feedback, we consider all possible user choices of indicating zero or more relevant documents from a set of 10 displayed documents. Examination of the effects of each user choice permits us to compute an upper-bound on the performance of each RF algorithm. We find that there is a significant variation in the upper-bound performance of the three RF algorithms and that the Bayesian algorithm approaches the best possible. Categories and Subject Descriptors H.3.3 Information Search and Retrieval ? relevance feedback General Terms Algorithms, Performance, Experimentation Keywords Relevance Feedback, Web Search, Evaluation
Vishwa Vinay, Kenneth R. Wood, Natasa Milic-Frayli
Added 22 Nov 2009
Updated 22 Nov 2009
Type Conference
Year 2005
Where WWW
Authors Vishwa Vinay, Kenneth R. Wood, Natasa Milic-Frayling, Ingemar J. Cox
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