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Experiments with Document Archive Size Detection

  • Shengli Wu
  • Forbes Gibb
  • Fabio Crestani
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2633)

Abstract

The size of a document archive is a very important parameter for resource selection in distributed information retrieval systems. In this paper, we present a method for automatically detecting the size (i.e. number of documents) of a document archive, in case the archive itself does not provided such information. In addition, a method for detecting the incremental change of the archive size is also presented, which can be useful for deciding if a resource description has become obsolete and needs to be regenerated. An experimental evaluation of these methods shows that they provide quite accurate information.

Keywords

Language Model Financial Time Wall Street Journal Incremental Change Information Retrieval System 
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

  • Shengli Wu
    • 1
  • Forbes Gibb
    • 1
  • Fabio Crestani
    • 1
  1. 1.Department of Computer and Information SciencesUniversity of StrathclydeGlasgow, ScotlandUK

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