A Survey on Fuzzy Association Rule Mining Methodologies
Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2013, Vol 15, Issue 6
Abstract
Fuzzy association rule mining (Fuzzy ARM) uses fuzzy logic to generate interesting association rules. These association relationships can help in decision making for the solution of a given problem. Fuzzy ARM is a variant of classical association rule mining. Classical association rule mining uses the concept of crisp sets. Because of this reason classical association rule mining has several drawbacks. To overcome those drawbacks the concept of fuzzy association rule mining came. Today there is a huge number of different types of fuzzy association rule mining algorithms are present in research works and day by day these algorithms are getting better. But as the problem domain is also becoming more complex in nature, continuous research work is still going on. In this paper, we have studied several well-known methodologies and algorithms for fuzzy association rule mining. Four important methodologies are briefly discussed in this paper which will show the recent trends and future scope of research in the field of fuzzy association rule mining.
Authors and Affiliations
Aritra Roy
Keywords
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