Fuzzy Formal Concept Analysis is a generalization of Formal Concept analysis (FCA) for modeling uncertain information and has been applied in recent years for supporting different activities of semantic web context. However Fuzzy FCA considers type-1 fuzzy rules and does not benefit the opportunities provided by type-2 fuzzy systems. The heterogeneity and imprecision of data on the internet in one hand and the need to extract intensively blurred information from the net for semantic web purposes, on the other hand, highlights the necessity for the development of type-2 fuzzy analytical system. Accordingly, this paper proposes an Interval Type-2 Fuzzy FCA system and applies it for similarity reasoning in the context of the semantic web.
['Hoda Safaeipour', 'M. H. Fazel Zarandi', 'I.B. Turksen']
Developing type-2 fuzzy FCA for similarity reasoning in the semantic web