Efficient mining of both positive and negative association rules

Publication Type:
Journal Article
Citation:
ACM Transactions on Information Systems, 2004, 22 (3), pp. 381 - 405
Issue Date:
2004-07-01
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This paper presents an efficient method for mining both positive and negative association rules in databases. The method extends traditional associations to include association rules of forms A ⇒ ¬B, ¬A ⇒ B, and ¬A ⇒ ¬B, which indicate negative associations between itemsets. With a pruning strategy and an interestingness measure, our method scales to large databases. The method has been evaluated using both synthetic and real-world databases, and our experimental results demonstrate its effectiveness and efficiency.
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