Comparing query logs and pseudo-relevance feedbackfor web-search query refinement

Authors:
Ryen W. White;Charles L. A. Clarke;Silviu Cucerzan
Affiliations:
Microsoft Corporation, Redmond, WA;University of Waterloo, Waterloo, Canada;Microsoft Corporation, Redmond, WA
Venue:
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Year:
2007

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Abstract

Query logs and pseudo-relevance feedback (PRF) offer ways in which terms to refine Web searchers' queries can be selected, offered to searchers, and used to improve search effectiveness. In this poster we present a study of these techniques that aims to characterize the degree of similarity between them across a set of test queries, and the same set broken out by query type. The results suggest that: (i) similarity increases with the amount of evidence provided to the PRF algorithm, (ii) similarity is higherwhen titles/snippets are used for PRF than full-text, and (iii) similarity is higher for navigational than informational queries. The findings have implications for the combined usage of query logs and PRF in generating query refinement alternatives.