When is query performance prediction effective?

Hauff, C. and Azzopardi, L. (2009) When is query performance prediction effective? In: 32nd International ACM SIGIR Conference on Research and Development in Information Retrieval, Boston, USA, 19-23 Jul 2009, pp. 829-830. (doi: 10.1145/1571941.1572150)

Abstract

The utility of Query Performance Prediction (QPP) methods is commonly evaluated by reporting correlation coefficients to denote how well the methods perform at predicting the retrieval performance of a set of queries. However, a quintessential question remains unexplored: how strong does the correlation need to be in order to realize an increase in retrieval performance? In this work, we address this question in the context of Selective Query Expansion (SQE) and perform a large-scale experiment. The results show that to consistently and predictably improve retrieval effectiveness in the ideal SQE setting, a Kendall's Tau correlation of tau>=0.5 is required, a threshold which most existing query performance prediction methods fail to reach.

• Item Type: Conference Proceedings
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Azzopardi, Dr Leif
• Authors: Hauff, C., and Azzopardi, L.
• Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
• College/School: College of Science and Engineering > School of Computing Science
• Journal Name: SIGIR '09: Proceedings of the 32nd International ACM SIGIR Conference on Research and Development in Information Retrieval