Navigating the user query space

Cummins, R., Lalmas, M., O’Riordan, C. and Jose, J.M. (2011) Navigating the user query space. Lecture Notes in Computer Science, 7024, pp. 380-385. (doi: 10.1007/978-3-642-24583-1_37)

Abstract

Query performance prediction (QPP) aims to automatically estimate the performance of a query. Recently there have been many attempts to use these predictors to estimate whether a perturbed version of a query will outperform the original version. In essence, these approaches attempt to navigate the space of queries in a guided manner. In this paper, we perform an analysis of the query space over a substantial number of queries and show that (1) users tend to be able to extract queries that perform in the top 5% of all possible user queries for a specific topic, (2) that post-retrieval predictors outperform pre-retrieval predictors at the high end of the query space. And, finally (3), we show that some post retrieval predictors are better able to select high performing queries from a group of user queries for the same topic.

• Item Type: Articles
• Additional Information: Presented at 18th International Symposium, SPIRE 2011, Pisa, Italy, October 17-21, 2011.
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Jose, Professor Joemon and Lalmas, Professor Mounia and Cummins, Dr Ronan
• Authors: Cummins, R., Lalmas, M., O’Riordan, C., and Jose, J.M.
• College/School: College of Science and Engineering > School of Computing Science
• Journal Name: Lecture Notes in Computer Science
• Publisher: Springer
• ISSN: 0302-9743