Bulletin of Computational Applied Mathematics (Bull CompAMa)
Integrating Fuzzy Formal Concept Analysis and Rough Set Theory for the Semantic Web
Formal Concept Analysis and Rough Set Theory provide two mathematical frameworks in information management which have been developed almost independently in the past. Currently, their integration is revealing very interesting in different research fields, such as knowledge discovery, data mining, information retrieval, elearning, and ontology engineering. In this paper, we show how Rough Set Theory can be employed in combination with a generalization of Formal Concept Analysis for modeling uncertainty information (Fuzzy Formal Concept Analysis) to perform Semantic Web search. In particular this paper presents an updated evaluation of a previous proposal of the author which has been addressed because of the increasing interest in this topic and, at the same time, the absence in the literature of significant proposals combining these two frameworks.
Keywords: Semantic Web; Fuzzy Formal Concept Analysis; Rough Set Theory.
Cite this paper:
Formica A., Integrating Fuzzy Formal Concept Analysis and Rough Set Theory for the Semantic Web.
Bull. Comput. Appl. Math. (Bull CompAMa),
Vol. 6, No. 2, Jul-Dec, pp.65-84, 2018.