Mining Local Association Rules from Temporal Data Set
In this paper, we present a novel approach for finding association rules from locally frequent itemsets using rough set and boolean reasoning. The rules mined so are termed as local association rules. The efficacy of the proposed approach is established through experiment over retail dataset that contains retail market basket data from an anonymous Belgian retail store.
KeywordsData mining Temporal data mining Local association rule mining Rough set Boolean reasoning
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