Genetic algorithms in relevance feedback: a second test and new contributions

  • Authors:
  • Cristina López-Pujalte;Vicente P. Guerrero-Bote;Félix de Moya-Anegón

  • Affiliations:
  • Library and Information Science Faculty, University of Extremadura, Alcazaba de Badajoz (Antiguo Hospital Militar), 06071 Badajoz, Spain;Library and Information Science Faculty, University of Extremadura, Alcazaba de Badajoz (Antiguo Hospital Militar), 06071 Badajoz, Spain;Library and Information Science Faculty, University of Granada, Campus Cartuja, 18071 Granada, Spain

  • Venue:
  • Information Processing and Management: an International Journal
  • Year:
  • 2003

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Abstract

The present work is the continuation of an earlier study which reviewed the literature on relevance feedback genetic techniques that follow the vector space model (the model that is most commonly used in this type of application), and implemented them so that they could be compared with each other as well as with one of the best traditional methods of relevance feedback--the Ide dec-hi method. We here carry out the comparisons on more test collections (Cranfield, CISI, Medline, and NPL), using the residual collection method for their evaluation as is recommended in this type of technique. We also add some fitness functions of our own design.