Fast discovery of association rules
Advances in knowledge discovery and data mining
Fundamenta Informaticae
Rough sets and association rule generation
Fundamenta Informaticae
Rough set algorithms in classification problem
Rough set methods and applications
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
The Representative Basis for Association Rules
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Handbook of data mining and knowledge discovery
Handbook of data mining and knowledge discovery
Fundamenta Informaticae
Order based genetic algorithms for the search of approximate entropy reducts
RSFDGrC'03 Proceedings of the 9th international conference on Rough sets, fuzzy sets, data mining, and granular computing
Short communication: Uncertainty measures for fuzzy relations and their applications
Applied Soft Computing
On Irreducible Descriptive Sets of Attributes for Information Systems
RSCTC '08 Proceedings of the 6th International Conference on Rough Sets and Current Trends in Computing
Rough Sets and Functional Dependencies in Data: Foundations of Association Reducts
Transactions on Computational Science V
RSFDGrC '07 Proceedings of the 11th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
Transactions on rough sets XII
Projected Gustafson-Kessel clustering algorithm and its convergence
Transactions on rough sets XIV
Association reducts: boolean representation
RSKT'06 Proceedings of the First international conference on Rough Sets and Knowledge Technology
Irreducible descriptive sets of attributes for information systems
Transactions on Rough Sets XI
Association reducts: complexity and heuristics
RSCTC'06 Proceedings of the 5th international conference on Rough Sets and Current Trends in Computing
The concept of reducts in pawlak three-step rough set analysis
Transactions on Rough Sets XVI
Relational Operations and Uncertainty Measure in Rough Relational Database
Fundamenta Informaticae
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We introduce the notion of an association reduct. It is an analogy to association rules at the level of global dependencies between the sets of attributes. Association reducts represent important complex relations, beyond usually considered “single attribute – single attribute” similarities. They can also express approximate dependencies in terms of, for instance, the information-theoretic measures. Finally, association reducts can be extracted from data using algorithms adapted from the domain of association rules and the theory of rough sets.