Computing a concept lattice from structured and fuzzy data

Author

Girard, Régis ; Ralambondrainy, H.

Author_Institution

Reunion Univ., France

Volume

1

fYear

1997

fDate

1-5 Jul 1997

Firstpage

135

Abstract

The problem of acquiring knowledge from a set of data is fundamental for humans to understand their experiences and to classify new observations. In this paper, we are concerned with acquiring concepts from data that may not be precisely or perfectly defined. We show the utility of lattice fuzzy sets to model uncertainty and imprecision for complex and structured data in rich domains such as ecology or botany. We propose an incremental algorithm to organize a given set of observations into a concept lattice. An application on data sponge illustrates the interest of the learning system proposed

Keywords

biology computing; data structures; database management systems; fuzzy set theory; learning systems; pattern classification; Hyalonema sponge; clustering; concept lattice; data structure; database management system; fuzzy data; fuzzy set theory; learning process; structured data; uncertainty modelling; Biological system modeling; Clustering algorithms; Clustering methods; Data analysis; Environmental factors; Fuzzy sets; Humans; Lattices; Learning systems; Pattern analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 1997., Proceedings of the Sixth IEEE International Conference on

Conference_Location

Barcelona

Print_ISBN

0-7803-3796-4

Type

conf

DOI

10.1109/FUZZY.1997.616358

Filename

616358