An Algorithm for Mining Multidimensional Fuzzy Association Rules
Abstract
Multidimensional association rule mining searches for interesting relationship among the values from different dimensions or 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.
Cite
@article{arxiv.0909.5166,
title = {An Algorithm for Mining Multidimensional Fuzzy Association Rules},
author = {Neelu Khare and Neeru Adlakha and K. R. Pardasani},
journal= {arXiv preprint arXiv:0909.5166},
year = {2009}
}
Comments
5 pages IEEE format, International Journal of Computer Science and Information Security, IJCSIS 2009, ISSN 1947 5500, Impact Factor 0.423, http://sites.google.com/site/ijcsis/