On generating all maximal independent sets
Information Processing Letters
Efficient algorithms for listing combinatorial structures
Efficient algorithms for listing combinatorial structures
Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Understanding class hierarchies using concept analysis
ACM Transactions on Programming Languages and Systems (TOPLAS)
Learning of Simple Conceptual Graphs from Positive and Negative Examples
PKDD '99 Proceedings of the Third European Conference on Principles of Data Mining and Knowledge Discovery
Using a Concept Lattice of Decomposition Slices for Program Understanding and Impact Analysis
IEEE Transactions on Software Engineering
Mining Non-Redundant Association Rules
Data Mining and Knowledge Discovery
Random walk biclustering for microarray data
Information Sciences: an International Journal
Top-down mining of frequent closed patterns from very high dimensional data
Information Sciences: an International Journal
Discovery of optimal factors in binary data via a novel method of matrix decomposition
Journal of Computer and System Sciences
Multi-adjoint t-concept lattices
Information Sciences: an International Journal
Comparison of Data Structures for Computing Formal Concepts
MDAI '09 Proceedings of the 6th International Conference on Modeling Decisions for Artificial Intelligence
Parallel algorithm for computing fixpoints of Galois connections
Annals of Mathematics and Artificial Intelligence
Evaluation of IPAQ questionnaires supported by formal concept analysis
Information Sciences: an International Journal
PKDD'06 Proceedings of the 10th European conference on Principle and Practice of Knowledge Discovery in Databases
Computing Formal Concepts by Attribute Sorting
Fundamenta Informaticae - Concept Lattices and Their Applications
Rough set model based on formal concept analysis
Information Sciences: an International Journal
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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.