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Ranking Structured Documents Using Utility Theory in the Bayesian Network Retrieval Model

  • Fabio Crestani
  • Luis M. de Campos
  • Juan M. Fernández-Luna
  • Juan F. Huete
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2857)

Abstract

In this paper a new method based on Utility and Decision theory is presented to deal with structured documents. The aim of the application of these methodologies is to refine a first ranking of structural units, generated by means of an Information Retrieval Model based on Bayesian Networks. Units are newly arranged in the new ranking by combining their posterior probabilities, obtained in the first stage, with the expected utility of retrieving them. The experimental work has been developed using the Shakespeare structured collection and the results show an improvement of the effectiveness of this new approach.

Keywords

Utility Function Bayesian Network Structural Unit Decision Theory Expected Utility 
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

  • Fabio Crestani
    • 1
  • Luis M. de Campos
    • 2
  • Juan M. Fernández-Luna
    • 2
  • Juan F. Huete
    • 2
  1. 1.Department of Computer and Information SciencesUniversity of StrathclydeGlasgowScotland, UK
  2. 2.Departamento de Ciencias de la Computación e Inteligencia Artificial, E.T.S.I. InformáticaUniversidad de GranadaGranadaSpain

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