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Fast algorithm for computing fixpoints of Galois connections induced by object-attribute relational data. (English) Zbl 1239.68070

Summary: Fixpoints of Galois connections induced by object-attribute data tables represent important patterns that can be found in relational data. Such patterns are used in several data mining disciplines including formal concept analysis, frequent itemset and association rule mining, and Boolean factor analysis. In this paper we propose efficient algorithm for listing all fixpoints of Galois connections induced by object-attribute data. The algorithm, called FCbO, results as a modification of Kuznetsov’s CbO in which we use more efficient canonicity test. We describe the algorithm, prove its correctness, discuss efficiency issues, and present an experimental evaluation of its performance and comparison with other algorithms.

MSC:

68T30 Knowledge representation
68T05 Learning and adaptive systems in artificial intelligence
06A15 Galois correspondences, closure operators (in relation to ordered sets)

Software:

AddIntent; UCI-ml; FCALGS
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References:

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