Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Mining association rules with multiple minimum supports
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Algorithms for association rule mining — a general survey and comparison
ACM SIGKDD Explorations Newsletter
Mining Frequent Patterns without Candidate Generation: A Frequent-Pattern Tree Approach
Data Mining and Knowledge Discovery
A Model-Based Frequency Constraint for Mining Associations from Transaction Data
Data Mining and Knowledge Discovery
Association rule and quantitative association rule mining among infrequent items
Proceedings of the 8th international workshop on Multimedia data mining: (associated with the ACM SIGKDD 2007)
Mining rare association rules in the datasets with widely varying items' frequencies
DASFAA'10 Proceedings of the 15th international conference on Database Systems for Advanced Applications - Volume Part I
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Rare association rules are the association rules consisting of rare items. It is difficult to mine rare association rules with the single minimum support based approaches such as Apri-ori and FP-growth as they suffer from rare item problem. In the literature, efforts has been made to extract rare association rules with multiple minimum supports. It was observed that the multiple minimum supports-based approach still suffers from performance problems. As a part of proposed work, we have analyzed the multiple minimum supports-based approach and proposed improved approaches for extracting rare association rules. Experimental results show that the proposed approaches are efficient.