Predicate Invention and the Revision of First-Order Concept Lattices
In previous work it was shown that Formal Concept Analysis (FCA) can provide a useful framework for adjustment of representational bias for classifier learning and the construction of taxonomical hierarchies. This used techniques of predicate invention from Inductive Logic Programming (ILP) to introduce new attributes and re-formulate object descriptions. Such re-formulation of the descriptions of objects forces revision of the concept lattice. Hence a definition of revision operators based on ILP operators was introduced and shown to generate correct updates. However, in knowledge representation it is often the case that first-order or relational concepts are useful. Although there are previously published approaches to using first-order representations in FCA, in this paper we present an approach to constructing formal concepts using first-order logic intended to allow the application of methods developed in ILP. A lattice revision operator for relational concepts is then defined based on an ILP method for predicate invention.
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