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Towards Ontological Structures Extraction from Folksonomies: An Efficient Fuzzy Clustering Approach

Author

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  • Marouf Zahia

    (EEDIS Laboratory, Djillali Liabes University of Sidi Bel Abbes, Sidi Bel Abbes, Algeria)

  • Benslimane Sidi Mohamed

    (EEDIS Laboratory, Djillali Liabes University of Sidi Bel Abbes, Sidi Bel Abbes, Algeria)

Abstract

Folksonomies are one of the technologies of Web 2.0 that permit users to annotate resources on the Web. In this paper, the authors propose an integrated approach to extract ontological structures from unstructured and semi-structured resources. Our proposal overcome limitations of existing approaches. It gives a formal, simple, and efficient solution to the tag clustering and disambiguation problem. Moreover, their approach doesn't need any ontology as an upper guide during the generation process. The generated ontology can be used to enhance various tasks such as ontology evolution and enrichment.

Suggested Citation

  • Marouf Zahia & Benslimane Sidi Mohamed, 2014. "Towards Ontological Structures Extraction from Folksonomies: An Efficient Fuzzy Clustering Approach," International Journal of Intelligent Information Technologies (IJIIT), IGI Global, vol. 10(4), pages 40-50, October.
  • Handle: RePEc:igg:jiit00:v:10:y:2014:i:4:p:40-50
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