Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Machine Learning
An Incremental Learning Algorithm for Constructing Decision Rules
RSKD '93 Proceedings of the International Workshop on Rough Sets and Knowledge Discovery: Rough Sets, Fuzzy Sets and Knowledge Discovery
Rough Sets and Knowledge Discovery: An Overview
RSKD '93 Proceedings of the International Workshop on Rough Sets and Knowledge Discovery: Rough Sets, Fuzzy Sets and Knowledge Discovery
Knowledge Bases Over Algebraic Models: Some Notes About Informational Equivalence
International Journal of Knowledge Management
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Ever since Data Mining first appeared, a considerable amount of algorithms, methods and techniques have been developed. As a result of research, most of these algorithms have proved to be more effective and efficient. For solving problems different algorithms are often compared. However, algorithms that use different approaches are not very often applied jointly to obtain better results. An approach based on the joining of a predictive model (rough sets) together with a link analysis model (the Apriori algorithm) is presented in this paper.