Why and How Knowledge Discovery Can Be Useful for Solving Problems with CBR

Amedeo Napoli (1)

1 ORPAILLEUR - Knowledge representation, reasonning

In this talk, we discuss and illustrate links existing between knowledge discovery in databases (KDD), knowledge representation and reasoning (KRR), and case-based reasoning (CBR). KDD techniques especially based on Formal Concept Analysis (FCA) are well formalized and allow the design of concept lattices from binary and complex data. These concept lattices provide a realistic basis for knowledge base organization and ontology engineering. More generally, they can be used for representing knowledge and reasoning in knowledge systems and CBR systems as well.

Mots clés: Case-Based Reasoning; Knowledge Discovery; Data Mining; Formal Concept Analysis

Domaines: Intelligence artificielle [cs.AI]

Amedeo Napoli. Why and How Knowledge Discovery Can Be Useful for Solving Problems with CBR. Case-Based Reasoning. Research and Development, 18th International Conference on Case-Based Reasoning, ICCBR 2010, Alessandria, Italy, July 19-22, 2010. Proceedings, 2010, Alessandria (Italie), France. pp.12-19. ⟨hal-00608016⟩