Computation of reducts of composed information systems
Fundamenta Informaticae - Special issue: rough sets
Fast discovery of association rules
Advances in knowledge discovery and data mining
Rules in incomplete information systems
Information Sciences: an International Journal
On semantic issues connected with incomplete information databases
ACM Transactions on Database Systems (TODS)
On Databases with Incomplete Information
Journal of the ACM (JACM)
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
On the Extension of Rough Sets under Incomplete Information
RSFDGrC '99 Proceedings of the 7th International Workshop on New Directions in Rough Sets, Data Mining, and Granular-Soft Computing
On possible rules and apriori algorithm in non-deterministic information systems
RSCTC'06 Proceedings of the 5th international conference on Rough Sets and Current Trends in Computing
RSFDGrC '09 Proceedings of the 12th International Conference on Rough Sets, Fuzzy Sets, Data Mining and Granular Computing
Dominance-based rough set approach for possibilistic information systems
RSFDGrC'11 Proceedings of the 13th international conference on Rough sets, fuzzy sets, data mining and granular computing
Relational Operations and Uncertainty Measure in Rough Relational Database
Fundamenta Informaticae
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A rule in a DeterministicInformationSystem(DIS) is often defined by an implicationτsuch that both support(τ) ≥αand accuracy(τ) ≥βhold for the threshold values ¿andß. In a Non-deterministicInformationSystem(NIS), there arederivedDISsdue to the informationincompleteness. The definition of a rule in a DISisextended to the lowerand upperapproximationsof a rule in a NIS. Thisdefinition explicitly handles non-deterministic information andincomplete information. To implement the utility programs for twoapproximations, Apriorialgorithm is extended. Even thoughthe number of derived DISsincreases in exponential order,this extended algorithm does not depend upon the number of derivedDISs. A prototype system is implemented, and this systemis applied to some data sets.