%0 Generic %1 roy2014introducing %A Roy, Aritra %A and Rajdeep Chatterjee, %B Int. Conf. on Recent Trends in Information, Telecommunication and Computing , ITC %D 2014 %I ACEEE (A Computer division of IDES) %K Association minin rule %T Introducing New Hybrid Rough Fuzzy Association Rule Mining Algorithm %U http://searchdl.org/public/conference/2014/ITC/101.pdf %X 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

@conference{roy2014introducing, abstract = {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}, added-at = {2014-03-21T10:09:58.000+0100}, author = {Roy, Aritra and and Rajdeep Chatterjee}, biburl = {https://www.bibsonomy.org/bibtex/2994f344b7b65c25d088f3ec09cdef046/idescitation}, booktitle = {Int. Conf. on Recent Trends in Information, Telecommunication and Computing , ITC}, interhash = {ba72830148e86a706b7b1029c94791e1}, intrahash = {994f344b7b65c25d088f3ec09cdef046}, keywords = {Association minin rule}, organization = {Institute of Doctors Engineers and Scientists}, publisher = {ACEEE (A Computer division of IDES)}, timestamp = {2014-03-21T10:09:58.000+0100}, title = {Introducing New Hybrid Rough Fuzzy Association Rule Mining Algorithm}, url = {http://searchdl.org/public/conference/2014/ITC/101.pdf}, year = 2014 }