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Term Proximity Scoring for Keyword-Based Retrieval Systems

  • Yves Rasolofo
  • Jacques Savoy
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2633)

Abstract

This paper suggests the use of proximity measurement in combination with the Okapi probabilistic model. First, using the Okapi system, our investigation was carried out in a distributed retrieval framework to calculate the same relevance score as that achieved by a single centralized index. Second, by applying a term-proximity scoring heuristic to the top documents returned by a keyword-based system, our aim is to enhance retrieval performance. Our experiments were conducted using the TREC8, TREC9 and TREC10 test collections, and show that the suggested approach is stable and generally tends to improve retrieval effectiveness especially at the top documents retrieved.

Keywords

Average Precision Retrieval Performance Term Pair Inverted File Document Score 
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 2003

Authors and Affiliations

  • Yves Rasolofo
    • 1
  • Jacques Savoy
    • 1
  1. 1.Université de NeuchâtelNeuchatelSwitzerland

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