Hypergeometric Language Model and Zipf-Like Scoring Function for Web Document Similarity Retrieval

  • Felipe Bravo-Marquez
  • Gaston L’Huillier
  • Sebastián A. Ríos
  • Juan D. Velásquez
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6393)

Abstract

The retrieval of similar documents in the Web from a given document is different in many aspects from information retrieval based on queries generated by regular search engine users. In this work, a new method is proposed for Web similarity document retrieval based on generative language models and meta search engines. Probabilistic language models are used as a random query generator for the given document. Queries are submitted to a customizable set of Web search engines. Once all results obtained are gathered, its evaluation is determined by a proposed scoring function based on the Zipf law. Results obtained showed that the proposed methodology for query generation and scoring procedure solves the problem with acceptable levels of precision.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Felipe Bravo-Marquez
    • 1
  • Gaston L’Huillier
    • 1
  • Sebastián A. Ríos
    • 1
  • Juan D. Velásquez
    • 1
  1. 1.Department of Industrial EngineeringUniversity of ChileSantiagoChile

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