Fast Factorization of Concept Lattices by Similarity: Solution and an Open Problem
نویسندگان
چکیده
An important problem in applications of formal concept analysis is a possibly large number of clusters extracted from data. Factorization is one of the methods being used to cope with the number of clusters. We present an algorithm for computing a factor lattice of a concept lattice from the data and a user-specified similarity threshold a. The elements of the factor lattice are collections of clusters which are pairwise similar in degree at least a. The presented algorithm computes the factor lattice directly from the data, without first computing the whole concept lattice and then computing the collections of clusters. We present theoretical insight and examples for demonstration, and an open problem.
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