Abstract
We present an approach to representation and structuring of theories and ontologies based on a formalism of propositional logic programs. Formal concept analysis is adopted to identify structure in theories. This structure, in the form of conjunctive concepts and the relations between them, is used for representation change in theories based on feature construction and iterative program transformation. Ontologies are represented as sets of propositional definite clauses containing named concepts having a superclass–subclass relationship derived from a concept lattice built using formal concept analysis. Logic programming methods are used to incrementally construct and revise such ontologies. An information compression measure is used to guide the operation of structuring theories and ontologies. The clauses defining the ontology are proved to preserve the relationships which hold between formal concepts in the concept lattice. This framework enables inheritance inference not possible from the structured theories alone. Experimental results are presented from an application to a sample of descriptions of computer science academics’ research interests and a reconstruction experiment on randomly generated theories with added noise.
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Bain, M. (2003). Inductive Construction of Ontologies from Formal Concept Analysis. In: Gedeon, T.(.D., Fung, L.C.C. (eds) AI 2003: Advances in Artificial Intelligence. AI 2003. Lecture Notes in Computer Science(), vol 2903. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24581-0_8
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DOI: https://doi.org/10.1007/978-3-540-24581-0_8
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