An Algorithm for Mining Multidimensional Fuzzy Association Rules

نویسندگان

  • Neelu Khare
  • Neeru Adlakha
  • K. R. Pardasani
چکیده

Multidimensional association rule mining searches for interesting relationship among the values from different dimensions/attributes in a relational database. In this method the correlation is among set of dimensions i.e., the items forming a rule come from different dimensions. Therefore each dimension should be partitioned at the fuzzy set level. This paper proposes a new algorithm for generating multidimensional association rules by utilizing fuzzy sets. A database consisting of fuzzy transactions, the Apriory property is employed to prune the useless candidates, itemsets. Keywordsinterdimension ; multidimensional association rules; fuzzy membership functions ;categories.

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عنوان ژورنال:
  • CoRR

دوره abs/0909.5166  شماره 

صفحات  -

تاریخ انتشار 2009