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A Literature Review of Association Rules in Mining

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A Literature Review of Association Rules in Mining

Abstract Mining association rules is an essential job for information discovery. Past transaction data can be analyzed to discover client behaviors such that the superiority of business decision can be improved. The approach of mining association rules focuses on discovering large item sets, which are groups of items that come into view together in a sufficient number of dealings. Association rules are if/then statements that help uncover relationships between seemingly unrelated data in a information repository. In this paper we will show by experimental results the behavior of apriori algorithm. Weshall describes the basic concepts of association rules mining, the basic model of mining association rules. Finally, this paper describes the association rules mining and its techniques.


Association rules mining is an important task in data mining. It is a popular and well researched method for discovering strong associations between variables in large databases.

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