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Navigating the User Query Space

  • Ronan Cummins
  • Mounia Lalmas
  • Colm O’Riordan
  • Joemon M. Jose
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7024)

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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Ronan Cummins
    • 1
  • Mounia Lalmas
    • 2
  • Colm O’Riordan
    • 3
  • Joemon M. Jose
    • 1
  1. 1.School of Computing ScienceUniversity of GlasgowUK
  2. 2.Yahoo! ResearchBarcelonaSpain
  3. 3.Dept. of Information TechnologyNational University of IrelandGalwayIreland

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