Interesting rules mining with deductive method

Wenxiang Dou*, Jinglu Hu, Gengfeng Wu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)


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.

Original languageEnglish
Title of host publicationICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings
Number of pages5
Publication statusPublished - 2009 Dec 1
EventICROS-SICE International Joint Conference 2009, ICCAS-SICE 2009 - Fukuoka, Japan
Duration: 2009 Aug 182009 Aug 21

Publication series

NameICCAS-SICE 2009 - ICROS-SICE International Joint Conference 2009, Proceedings


OtherICROS-SICE International Joint Conference 2009, ICCAS-SICE 2009

ASJC Scopus subject areas

  • Information Systems
  • Control and Systems Engineering
  • Industrial and Manufacturing Engineering


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