Zusammenfassung
Association rules shows us interesting associations among data items. It means
tha
t an association rule clearly defines that how a data item is related or associated with
another data item. That is why these types of rules are called Association rules. And the
procedure by which these rules are extracted and managed is known as Associat
ion rule
mining. Classical association rule mining had many limitations. As a result Fuzzy
association rule mining (Fuzzy ARM) came. But Fuzzy ARM also has its limitations like
redundant rule generation and inefficiency in large mining tasks. After that Ro
ugh
association rule mining (Rough ARM) came which seemed to be a good alternative of Fuzzy
association rule mining in terms of performance. But day by day our mining task is
becoming huge. So, performing mining task efficiently and accurately over a large
dataset is
still a big challenge to us. In this paper we have presented a new hybrid mining method
which has incorporated the concepts of both rough set theory and fuzzy set theory for
association rule generation
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