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SIGIR
2009
ACM

Reducing long queries using query quality predictors

14 years 6 months ago
Reducing long queries using query quality predictors
Long queries frequently contain many extraneous terms that hinder retrieval of relevant documents. We present techniques to reduce long queries to more effective shorter ones that lack those extraneous terms. Our work is motivated by the observation that perfectly reducing long TREC description queries can lead to an average improvement of 30% in mean average precision. Our approach involves transforming the reduction problem into a problem of learning to rank all sub-sets of the original query (sub-queries) based on their predicted quality, and select the top sub-query. We use various measures of query quality described in the literature as features to represent sub-queries, and train a classifier. Replacing the original long query with the top-ranked subquery chosen by the ranking classifier results in a statistically significant average improvement of 8% on our test sets. Analysis of the results shows that query reduction is wellsuited for moderately-performing long queries, an...
Giridhar Kumaran, Vitor R. Carvalho
Added 28 May 2010
Updated 28 May 2010
Type Conference
Year 2009
Where SIGIR
Authors Giridhar Kumaran, Vitor R. Carvalho
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