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SAC
2010
ACM

Background knowledge in formal concept analysis: constraints via closure operators

9 years 6 months ago
Background knowledge in formal concept analysis: constraints via closure operators
The aim of this short paper is to present a general method of using background knowledge to impose constraints in conceptual clustering of object-attribute relational data. The proposed method uses the background knowledge to extract only particular clusters from the input data—those which are compatible with the background knowledge and thus satisfy the constraint. As a result, the method allows for extracting less clusters in a shorter time which are in addition more interesting. The paper presents the idea of constraints formalized by means of closure operators and introduces such constraints to a particular clustering technique, namely to formal concept analysis. Among the benefits of the presented approach are its versatility (the approach covers several examples studied before, e.g. extraction of closed frequent itemsets in generation of non-redundant association rules) and computational efficiency (polynomial time-delay algorithm for computing constrained clusters). Due to s...
Radim Belohlávek, Vilém Vychodil
Added 17 May 2010
Updated 17 May 2010
Type Conference
Year 2010
Where SAC
Authors Radim Belohlávek, Vilém Vychodil
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