Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Using association rules for product assortment decisions: a case study
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
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
Methods and Problems in Data Mining
ICDT '97 Proceedings of the 6th International Conference on Database Theory
Mining Frequent Patterns without Candidate Generation: A Frequent-Pattern Tree Approach
Data Mining and Knowledge Discovery
Mining with rarity: a unifying framework
ACM SIGKDD Explorations Newsletter - Special issue on learning from imbalanced datasets
Introduction to the special issue on successful real-world data mining applications
ACM SIGKDD Explorations Newsletter
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)
Improved approaches to mine rare association rules in transactional databases
Proceedings of the Fourth SIGMOD PhD Workshop on Innovative Database Research
Towards efficient mining of periodic-frequent patterns in transactional databases
DEXA'10 Proceedings of the 21st international conference on Database and expert systems applications: Part II
Proceedings of the 14th International Conference on Extending Database Technology
An efficient approach to mine rare association rules using maximum items' support constraints
BNCOD'10 Proceedings of the 27th British national conference on Data Security and Security Data
Fuzzy association rule mining approaches for enhancing prediction performance
Expert Systems with Applications: An International Journal
International Journal of Security and Networks
An improved neighborhood-restricted association rule-based recommender system
ADC '13 Proceedings of the Twenty-Fourth Australasian Database Conference - Volume 137
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Rare association rule is an association rule consisting of rare items. It is difficult to mine rare association rules with a single minimum support (minsup) constraint because low minsup can result in generating too many rules in which some of them can be uninteresting. In the literature, minimum constraint model using “multiple minsup framework” was proposed to efficiently discover rare association rules. However, that model still extracts uninteresting rules if the items’ frequencies in a dataset vary widely. In this paper, we exploit the notion of “item-to-pattern difference” and propose multiple minsup based FP-growth-like approach to efficiently discover rare association rules. Experimental results show that the proposed approach is efficient.