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A Survey on Association Rule Mining

D. Sasikala, Dr.K. Premalatha, S. Logeswari


Association rule mining is a popular and well researched method to discover interesting relations between the itemsets in large databases. Association rules show attributes value conditions that occur frequently together in a given dataset. Mining Association rules from the databases has the overhead in generating interesting rules, which includes rare itemsets, mining interesting rules from large databases and generation of strong associations. This review concentrates on improving the performance of Apriori, generating interesting Association rules using large databases, Quantitative Association rule mining and optimizing the Association rules. It also states various techniques used in Association rule generation process.


Association Rule Mining, Support, Confidence, Alternate Measures, Particle Swarm Optimization, Quantitative Associations.

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