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Relational Crossover in Evolutionary Ontologies

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10th International Conference on Soft Computing Models in Industrial and Environmental Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 368))

Abstract

In this paper we introduce a new genetic operator, namely relational crossover applied to evolutionary ontologies recently defined. Also we demonstrate that the relations preserve properties like reflexivity, irreflexivity, symmetry, antisymmetry, asymmetry, transitivity after applying relational crossover operator. Applying such an operator in the evolutionary process induces an important variation in the population, which is relevant for a better exploration of the ontological space.

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Acknowledgments

The research leading to these results has received funding from the European Communitys Seventh Framework Programme under grant agreement No609143 Project ProSEco.

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Authors and Affiliations

  1. Department of Electrical Engineering, Technical University of Cluj-Napoca, North University Centre of Baia Mare, Baia Mare, Romania

    Oliviu Matei

  2. Department of Automation, Technical University of Cluj-Napoca, Cluj-Napoca, Romania

    Diana Contraş & Honoriu Vălean

Authors
  1. Oliviu Matei
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  2. Diana Contraş
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  3. Honoriu Vălean
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Corresponding author

Correspondence to Oliviu Matei .

Editor information

Editors and Affiliations

  1. Department of Civil Engineering, University of Burgos, Burgos, Spain

    Álvaro Herrero

  2. C/ López Bravo 70, Pol. Ind. Villalonquejar, Technological Institute of Castilla y León, Burgos, Spain

    Javier Sedano

  3. Department of Civil Engineering, University of Burgos, Burgos, Spain

    Bruno Baruque

  4. University of Salamanca, Salamanca, Spain

    Héctor Quintián

  5. University of Salamanca, Salamanca, Spain

    Emilio Corchado

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Matei, O., Contraş, D., Vălean, H. (2015). Relational Crossover in Evolutionary Ontologies. In: Herrero, Á., Sedano, J., Baruque, B., Quintián, H., Corchado, E. (eds) 10th International Conference on Soft Computing Models in Industrial and Environmental Applications. Advances in Intelligent Systems and Computing, vol 368. Springer, Cham. https://doi.org/10.1007/978-3-319-19719-7_15

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  • DOI: https://doi.org/10.1007/978-3-319-19719-7_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-19718-0

  • Online ISBN: 978-3-319-19719-7

  • eBook Packages: EngineeringEngineering (R0)

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