In this paper we introduce a novel approach for query performance prediction based on ranking list scores dispersion. Starting from the hypothesis that different score distributions appear for good and poor performance queries, we introduce a set of measures that capture these differences between both types of distributions. The use of measures based on standard deviation of ranking list scores, as a prediction value, shows a significant correlation degree in terms of average precision. © 2009 Springer Berlin Heidelberg.
CITATION STYLE
Pérez-Iglesias, J., & Araujo, L. (2009). Ranking list dispersion as a query performance predictor. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5766 LNCS, pp. 371–374). https://doi.org/10.1007/978-3-642-04417-5_42
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