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Interesting Rules Mining with Deductive Method
Wenxiang Dou,Jinglu Hu,Gengfeng Wu 제어로봇시스템학회 2009 제어로봇시스템학회 국제학술대회 논문집 Vol.2009 No.8
In this paper, we propose a novel rule deductive method to mine the real demanded association rules for any given user. This method does not like the most existing methods that mine frequent itemsets starting from candidate two-itemsets to candidate (n-1)-itemsets with inductive method and produce huge rough rules on these frequent itemsets. On the contrary, it avoids producing huge amounts of frequent itemsets contained by their upper long frequent itemsets and can interact with users by making them pick up their interested items to deduce the final interesting association rules. Moreover, it can do dynamic response to users in any time when users want to check whether their interested frequent itemsets have been founded. Its several dynamic response strategies have been proposed. These dynamic response algorithms can find most long frequent itemsets in initial time. Therefore, users can find their interested rules in short time with high probability. So, our method also can be used applied in online data mining.
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