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Discovering taxonomies in Wikipedia by means of grammatical evolution

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Abstract

This work applies grammatical evolution to identify taxonomic hierarchies of concepts from Wikipedia. Each article in Wikipedia covers a topic and is cross-linked by hyperlinks that connect related topics. Hierarchical taxonomies and their generalization to ontologies are a highly useful resource for many applications since they enable semantic search and reasoning. Thus, the automatic identification of taxonomies composed of concepts associated with linked Wikipedia pages has attracted much attention. We have developed a system which arranges a set of Wikipedia concepts into a taxonomy. This technique is based on the relationships among a set of features extracted from the contents of the Wikipedia pages. We have used a grammatical evolution algorithm to discover the best way of combining the considered features in an explicit function. Candidate functions are evaluated by applying a genetic algorithm to approximate the optimal taxonomy that the function can provide for a number of training cases. The fitness is computed as an average of the precision obtained by comparing, for the set of training cases, the taxonomy provided by the evaluated function with the reference one. Experimental results show that the proposal is able to provide valuable functions to find high-quality taxonomies.

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Notes

  1. http://download.wikimedia.org/enwiki/.

  2. They are available at http://nlp.uned.es/~lurdes/wikipedia_data.

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Acknowledgements

This work has been partially supported by the Spanish Ministry of Science and Innovation within the projects EXTRECM (TIN2013-46616-C2-2-R) and PROSA-MED (TIN2016-77820-C3-2-R), as well as by the Universidad Nacional de Educación a Distancia (UNED) through the FPI-UNED 2013 Grant. The authors would like to thank the referees for their valuable comments which led to improvements in the paper.

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  1. Universidad Nacional de Educación a Distancia (UNED), Madrid, Spain

    Lourdes Araujo, Juan Martinez-Romo & Andrés Duque

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  1. Lourdes Araujo
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  2. Juan Martinez-Romo
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  3. Andrés Duque
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Correspondence to Lourdes Araujo.

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Lourdes Araujo declares that she has no conflict of interest. Juan Martinez-Romo declares that he has no conflict of interest. Andres Duque declares that he has no conflict of interest.

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This article does not contain any studies with human participants or animals performed by any of the authors.

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Communicated by V. Loia.

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Araujo, L., Martinez-Romo, J. & Duque, A. Discovering taxonomies in Wikipedia by means of grammatical evolution. Soft Comput 22, 2907–2919 (2018). https://doi.org/10.1007/s00500-017-2544-4

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