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A Study on Using Genetic Niching for Query Optimisation in Document Retrieval

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Book cover Advances in Information Retrieval (ECIR 2002)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2291))

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Abstract

This paper presents a new genetic approach for query optimisation in document retrieval. The main contribution of the paper is to show the effectiveness of the genetic niching technique to reach multiple relevant regions of the document space. Moreover, suitable merging procedures have been proposed in order to improve the retrieval evaluation. Experimental results obtained using a TREC sub-collection indicate that the proposed approach is promising for applications.

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Author information

Authors and Affiliations

  1. IRIT SIG Université de Toulouse III, 118 Route de Narbonne, 31062, Toulouse, France

    Mohand Boughanem

  2. ISYCOM/ GRIMM Université de Toulouse II, 5 Allées A. Machado, 31058, Toulouse Cedex, France

    Lynda Tamine

Authors
  1. Mohand Boughanem
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  2. Lynda Tamine
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Editor information

Editors and Affiliations

  1. Department of Computer and Information Sciences, University of Strathclyde, 26 Richmond Street, G1 1XH, Glasgow, UK

    Fabio Crestani

  2. School of Information and Communication Technologies, University of Paisley, High Street, PA1 2BE, Paisley, UK

    Mark Girolami

  3. Computing Science Department, University of Glasgow, 17 Lilybank Gardens, G12 8RZ, Glasgow, UK

    Cornelis Joost van Rijsbergen

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© 2002 Springer-Verlag Berlin Heidelberg

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Boughanem, M., Tamine, L. (2002). A Study on Using Genetic Niching for Query Optimisation in Document Retrieval. In: Crestani, F., Girolami, M., van Rijsbergen, C.J. (eds) Advances in Information Retrieval. ECIR 2002. Lecture Notes in Computer Science, vol 2291. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45886-7_10

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  • DOI: https://doi.org/10.1007/3-540-45886-7_10

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-43343-9

  • Online ISBN: 978-3-540-45886-9

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