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

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

Marouf Zahia, Benslimane Sidi Mohamed
Copyright: © 2014 |Volume: 10 |Issue: 4 |Pages: 11
ISSN: 1548-3657|EISSN: 1548-3665|EISBN13: 9781466654822|DOI: 10.4018/ijiit.2014100103
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MLA

Zahia, Marouf, and Benslimane Sidi Mohamed. "Towards Ontological Structures Extraction from Folksonomies: An Efficient Fuzzy Clustering Approach." IJIIT vol.10, no.4 2014: pp.40-50. https://doi.org/10.4018/ijiit.2014100103

APA

Zahia, M. & Mohamed, B. S. (2014). Towards Ontological Structures Extraction from Folksonomies: An Efficient Fuzzy Clustering Approach. International Journal of Intelligent Information Technologies (IJIIT), 10(4), 40-50. https://doi.org/10.4018/ijiit.2014100103

Chicago

Zahia, Marouf, and Benslimane Sidi Mohamed. "Towards Ontological Structures Extraction from Folksonomies: An Efficient Fuzzy Clustering Approach," International Journal of Intelligent Information Technologies (IJIIT) 10, no.4: 40-50. https://doi.org/10.4018/ijiit.2014100103

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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.

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