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Survey on the Efficient Hashing Techniques in Association Rule Mining

L. Padmavathy, V. Umarani


Association rule mining (ARM) is one of the most important techniques in data mining. The task is to find relationship between presences of various items in a given database. Frequent itemset mining plays an important role in data mining and also used to form association rules. A rule is represented as A=>B, where A and B are individual items in the database. Many business applications focus on discovery of frequent itemsets and association rules in order to improve their strategy. Association rule mining is efficiently improved by using various techniques. One of the widely used techniques among them is Hashing technique. Hashing technique utilizes hash tables to store itemsets and reduce the complexity of deriving association rules from large databases. This paper focus on how to improve the efficiency of association rules based on hashing technique.


Association Rules, Frequent Itemset, Hashing, and Collisions

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