出版社：Academy & Industry Research Collaboration Center (AIRCC)
摘要：Mining association rules is one of the most important data mining tasks. Its purpose is togenerate intelligible relations between attributes in a database. However, its use in practice isdifficult and still raises several challenges, in particular, the number of learned rules is oftenvery large. Several techniques for reducing the number of rules have been proposed asmeasures of quality, syntactic filtering constraints, etc. However, these techniques do not limitthe shortcomings of these methods. In this paper, we propose a new approach to mineassociation, assisted by a Boolean modeling of results in order to mitigate the shortcomingsmentioned above and propose a cellular automaton based on a boolean process for mining,optimizing, managing and representing of the learned rules.
关键词：Cellular automaton; Data mining; Association Rules; Boolean modeling; Apriori-Cell
