Abstract
The concept of informative base for association rules is the subject of many approaches. However, these approaches are based on positive rules but not on negative rules, and this with the less selective support-confidence pair. So that, these positive rules are not enough to cover all needs in context of Big Data, it also needs the negative association rules. In order to overcome these limitations, we propose a new approach for positive and negative association rules using the new selective pair, support -M GK . We also introduce NONREDRULES algorithm for mining all informative association rules. The experimental evaluation on the reference databases presents the extensive feasibility of our approach on the context of Big Data.
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