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Towards Normalizing the Edit Distance Using a Genetic Algorithms–Based Scheme

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Advanced Data Mining and Applications (ADMA 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7713))

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Abstract

The normalized edit distance is one of the distances derived from the edit distance. It is useful in some applications because it takes into account the lengths of the two strings compared. The normalized edit distance is not defined in terms of edit operations but rather in terms of the edit path. In this paper we propose a new derivative of the edit distance that also takes into consideration the lengths of the two strings, but the new distance is related directly to the edit distance. The particularity of the new distance is that it uses the genetic algorithms to set the values of the parameters it uses. We conduct experiments to test the new distance and we obtain promising results.

This work was carried out during the tenure of an ERCIM “Alain Bensoussan” Fellowship Programme. This Programme is supported by the Marie-Curie Co-funding of Regional, National and International Programmes (COFUND) of the European Commission.

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Muhammad Fuad, M.M. (2012). Towards Normalizing the Edit Distance Using a Genetic Algorithms–Based Scheme. In: Zhou, S., Zhang, S., Karypis, G. (eds) Advanced Data Mining and Applications. ADMA 2012. Lecture Notes in Computer Science(), vol 7713. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35527-1_40

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  • DOI: https://doi.org/10.1007/978-3-642-35527-1_40

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-35526-4

  • Online ISBN: 978-3-642-35527-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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