The combination and evaluation of query performance prediction methods

Hauff, C., Azzopardi, L. and Hiemstra, D. (2009) The combination and evaluation of query performance prediction methods. Lecture Notes in Computer Science, 5478, pp. 301-312. (doi: 10.1007/978-3-642-00958-7_28)

Abstract

In this paper, we examine a number of newly applied methods for combining pre-retrieval query performance predictors in order to obtain a better prediction of the query’s performance. However, in order to adequately and appropriately compare such techniques, we critically examine the current evaluation methodology and show how using linear correlation coefficients (i) do not provide an intuitive measure indicative of a method’s quality, (ii) can provide a misleading indication of performance, and (iii) overstate the performance of combined methods. To address this, we extend the current evaluation methodology to include cross validation, report a more intuitive and descriptive statistic, and apply statistical testing to determine significant differences. During the course of a comprehensive empirical study over several TREC collections, we evaluate nineteen pre-retrieval predictors and three combination methods.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Azzopardi, Dr Leif
• Authors: Hauff, C., Azzopardi, L., and Hiemstra, D.
• Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
• College/School: College of Science and Engineering > School of Computing Science
• Journal Name: Lecture Notes in Computer Science
• Publisher: Springer
• ISSN: 0302-9743
• ISSN (Online): 1611-3349