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European Conference on Information Retrieval

ECIR 2003: Advances in Information Retrieval pp 511–519Cite as

Generating Extracts with Genetic Algorithms

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2633))

Abstract

This paper describes an application of genetic algorithms for text summarisation. We have built a sentence extraction algorithm that overcomes some of the drawbacks of traditional sentence extractors, and takes into consideration different features of the summaries. The fitness function can be easily modified in order to incorporate features such as user modelling and adaptation. The system has been evaluated with standard procedures, and the obtained results are very good.

This work has been sponsored by CICYT, project number TIC2001-0685-C02-01.

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Author information

Authors and Affiliations

  1. Computer Science Department, Universidad Autónoma de Madrid, 28049, Madrid, Spain

    Enrique Alfonseca & Pilar Rodríguez

Authors
  1. Enrique Alfonseca
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  2. Pilar Rodríguez
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Editor information

Editors and Affiliations

  1. Instituto di Scienza e Tecnologie dell’Informazione, Consiglio Nazionale delle Ricerche, Via Giuseppe Moruzzi, 1, 56124, Pisa, Italy

    Fabrizio Sebastiani

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© 2003 Springer-Verlag Berlin Heidelberg

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Alfonseca, E., Rodríguez, P. (2003). Generating Extracts with Genetic Algorithms. In: Sebastiani, F. (eds) Advances in Information Retrieval. ECIR 2003. Lecture Notes in Computer Science, vol 2633. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36618-0_37

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  • DOI: https://doi.org/10.1007/3-540-36618-0_37

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-01274-0

  • Online ISBN: 978-3-540-36618-8

  • eBook Packages: Springer Book Archive

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