Fuzzy Formal Concept Analysis

Looking for equivalence between two soft concept hierarchies

When faced with large volumes of information, it is natural to adopt a granular approach by grouping together related items into categories. Frequently, this is extended to a hierarchy, with progressively finer division as one moves down the hierarchy. The widespread use of hierarchical organisation suggests that this is a natural approach for humans, as is the use of fuzzy categories rather than mutually exclusive crisp categories.

Formal concept analysis (FCA) is a way of extracting hidden structure (hierarchical) from a dataset in object-attribute-value form. This work focuses on extracting a hierarchy that is implicit in a data source, and mining different hierarchies.

This work is part of a project sponsored by BT Intelligent Systems Research Centre.