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ECIR
2008
Springer

Using Coherence-Based Measures to Predict Query Difficulty

8 years 3 months ago
Using Coherence-Based Measures to Predict Query Difficulty
Abstract. We investigate the potential of coherence-based scores to predict query difficulty. The coherence of a document set associated with each query word is used to capture the quality of a query topic aspect. A simple query coherence score, QC-1, is proposed that requires the average coherence contribution of individual query terms to be high. Two further query scores, QC-2 and QC-3, are developed by constraining QC1 in order to capture the semantic similarity among query topic aspects. All three query coherence scores show the correlation with average precision necessary to make them good predictors of query difficulty. Simple and efficient, the measures require no training data and are competitive with language model-based clarity scores.
Jiyin He, Martha Larson, Maarten de Rijke
Added 29 Oct 2010
Updated 29 Oct 2010
Type Conference
Year 2008
Where ECIR
Authors Jiyin He, Martha Larson, Maarten de Rijke
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