Association Rule Generation using Pattern Mining Apriori Technique

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Amit Verma, Raman Kumar


The Apriori algorithms is a most powerful and influential algorithm used in mining of association rules. This works on the concept of identifying the frequent datasets from some transactional database. Some association rules are derived from these frequent sets, these derived rules must satisfy some criteria like minimum support value and confidence threshold etc. [1, 2]. The large batches of data need to be refined and filter to make use of it for some specific purposes. These purposes can be helpful in decision making processes of business environments. Useful patterns can be searched in large data batches which can further be used in business to learn more about the customers so that more useful and effective marketing strategies can be developed, cost can be reduced and sales can be increased. In this paper, we will study the analytical approach generally called frequent pattern mining, previously known as ‘association’ and explain study of how association rules are generated using the concept of Apriori Algorithm.

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