Rules in incomplete information systems
Information Sciences: an International Journal
On semantic issues connected with incomplete information databases
ACM Transactions on Database Systems (TODS)
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
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
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A framework of Non-deterministicInformationSystems(NISs) is known well for handling information incompleteness in Deter- ministicInformationSystems(DISs). Apriori algorithm for the standard tables or DISsis also known as an algorithm to generate rules, which are characterized by criteria, supportand accuracy. This paper extends Apriori algorithm in DISsto Apriori algorithm in NISs. This extended Apriori algorithm employs criteria, minimumsupportand minimumaccuracyin NISs, and generates rules under the worst condition. A software tool is also implemented.