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Inferring Query Performance Using Pre-retrieval Predictors

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String Processing and Information Retrieval (SPIRE 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3246))

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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.

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He, B., Ounis, I. (2004). Inferring Query Performance Using Pre-retrieval Predictors. In: Apostolico, A., Melucci, M. (eds) String Processing and Information Retrieval. SPIRE 2004. Lecture Notes in Computer Science, vol 3246. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30213-1_5

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  • DOI: https://doi.org/10.1007/978-3-540-30213-1_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-23210-0

  • Online ISBN: 978-3-540-30213-1

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