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Inferring Query Performance Using Pre-retrieval Predictors

  • Ben He
  • Iadh Ounis
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3246)

Abstract

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 a set of predictors of query performance, which can be generated prior to the retrieval process. The linear and non-parametric correlations of the predictors with query performance are thoroughly assessed on the TREC disk4 and disk5 (minus CR) collections. 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.

Keywords

Average Precision Query Term Query Expansion Information Retrieval System Relevance Score 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Ben He
    • 1
  • Iadh Ounis
    • 1
  1. 1.Department of Computing ScienceUniversity of Glasgow 

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