A SURVEY ON FREQUENT ITEM SET MINING FOR LARGE TRANSACTIONAL DATA

Abstract

In the decision making process the Data Analytics plays an important role. The Insights that are obtained from pattern analysis gives many benefits like cost cutting, good revenue, and better competitive advantage. On the other hand the patterns of frequent itemsets that are hidden consume more time for extraction when data increases over time. However less memory consumption is required for mining the patterns of frequent itemsets because of heavy computation. Therefore, an algorithm required must be efficient for mining the patterns of the frequent itemsets that are hidden which takes less memory with short run time. This paper presents a review of different algorithms for finding Frequent Patterns so that a more efficient algorithm for finding frequent items sets can be developed.