A First Study on What MDL Can Do for FCA

Tatiana Makhalova (1, 2) , Sergei O. Kuznetsov (1) , Amedeo Napoli (2)

1 CS-HSE - Faculty of Computer Science [Moscow]
2 ORPAILLEUR - Knowledge representation, reasonning

Formal Concept Analysis can be considered as a classification engine able to build classes of objects with a description or concepts and to organize these concepts within a concept lattice. The concept lattice can be navigated for selecting significant concepts. Then the problem of finding significant concepts among the potential exponential number of concepts arises. Some measures exist that can be used for focusing on interesting concepts such as support, stability, and other. MDL (mini-mum description length) is also a good candidate that was rarely used in FCA by now for such objective. In this paper we argue that MDL can give FCA practitioners a good measure for selecting significant and representative concepts.

Domaines: Informatique [cs]; Intelligence artificielle [cs.AI]

Tatiana Makhalova, Sergei O. Kuznetsov, Amedeo Napoli. A First Study on What MDL Can Do for FCA. CLA 2018 - The 14th International Conference on Concept Lattices and Their Applications, Jun 2018, Olomouc, Czech Republic. ⟨hal-01888453⟩