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Space-Limited Ranked Query Evaluation Using Adaptive Pruning

  • Nicholas Lester
  • Alistair Moffat
  • William Webber
  • Justin Zobel
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3806)

Abstract

Evaluation of ranked queries on large text collections can be costly in terms of processing time and memory space. Dynamic pruning techniques allow both costs to be reduced, at the potential risk of decreased retrieval effectiveness. In this paper we describe an improved query pruning mechanism that offers a more resilient tradeoff between query evaluation costs and retrieval effectiveness than do previous pruning approaches.

Keywords

Mean Average Precision Query Evaluation Retrieval Effectiveness Posting List Query Stream 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Nicholas Lester
    • 1
  • Alistair Moffat
    • 2
  • William Webber
    • 2
  • Justin Zobel
    • 1
  1. 1.School of Computer Science and Information TechnologyRMIT UniversityAustralia
  2. 2.Department of Computer Science and Software EngineeringThe University of MelbourneAustralia

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