Concept Similarity in Formal Concept Analysis with many-valued contexts

Formal Concept Analysis (FCA) is a mathematical framework whichcan also support critical activities for the development of the Semantic Web. Oneof them is represented by Similarity Reasoning, i.e., the identification of differentconcepts that are semantically close, that allows users to retrieve information onthe Web more efficiently.In order to model uncertainty information, in this paper FCA with many-valuedcontexts is addressed, where attribute values are intervals, which is referred toas FCA with Interordinal scaling (IFCA). In particular, a method for evaluatingconcept similarity in IFCA is proposed, which is a problem that has not beenadequately investigated, although the increasing interest in the literature in thistopic.