The Galois lattice approach has been shown to provide a rich framework for the study of monothetic formal concepts within the context of an object by attribute correspondence. Yet, the approach is hampered by two problems: First, even for data sets of moderate size the Galois lattice is usually very complex. Second, small modifications of the correspondence under study (e.g., due to error) may lead to considerable modifications of the lattice. This paper presents a procedure to construct an approximate Galois lattice with limited order and length for a given binary correspondence. The procedure, which is based on Boolean matrix theory, makes use of an algorithm for Boolean factor analysis. Goodness-of-recovery results from a simulation study suggest that it allows one to retrieve a true correspondence from error-perturbed data.
[1]
Michael Luxenburger,et al.
Implications partielles dans un contexte
,
1991
.
[2]
W. Dixon,et al.
BMDP statistical software
,
1983
.
[3]
Rudolf Wille,et al.
Line diagrams of hierarchical concept systems
,
1984
.
[4]
R. Wille,et al.
Aspects of Finite Lattices
,
1977
.
[5]
Ryszard S. Michalski,et al.
Categories and Concepts: Theoretical Views and Inductive Data Analysis
,
1993
.
[6]
Vincent Duquenne,et al.
The core of finite lattices
,
1991
.
[7]
Alain Guénoche,et al.
Galois approach to the induction of concepts
,
1993
.
[8]
P. Boeck,et al.
Hierarchical classes: Model and data analysis
,
1988
.