An Approach to Discover Frequent Itemset and Promising Itemset Using Association Rule Mining

Computer Engineering

Data mining is part of KDD (knowledge discovery process). It is used to discover interesting data from large amount of data. One of the major concept of data mining is association rule mining and frequent itemset mining. Proposed approach is used to discover frequent itemset and promising frequent itemset and keep only useful data in database. So size of database is reduced. Frequent itemset is itemset having frequently Occurrence in transaction database. Promising item set is item set became frequent in nearest future. By using promising itemset list avoid rescanning of original database. In dynamic database only scan new inserted or increment data in database. Based on this frequent item set generate rule used in decision making strategy in retail business or many application.

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