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Query performance prediction
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DOI：10.1016/j.is.2005.11.003.png)
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Abstract
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The prediction of query performance is an interesting and important issue in Information Retrieval (IR). Current predictors involve the use of relevance scores, which are time-consuming to compute. Therefore, current predictors are not very suitable for practical applications. In this paper, we study six predictors of query performance, which can be generated prior to the retrieval process without the use of relevance scores. As a consequence, the cost of computing these predictors is marginal. The linear and non-parametric correlations of the proposed predictors with query performance are thoroughly assessed on the Text REtrieval Conference (TREC) disk4 and disk5 (minus CR) collection with the 249 TREC topics that were used in the recent TREC2004 Robust Track. According to the results, some of the proposed predictors have significant correlation with query performance, showing that these predictors can be useful to infer query performance in practical applications. (C) 2005 Elsevier B.V. All rights reserved.
Keywords:
query performance prediction
information retrieval
experiments
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