UTILITY SENTIENT FREQUENT ITEM SET MINING AND ASSOCIATION RULE MINING: A LITERATURE SURVEY AND COMPARATIVE STUDY
Shashi Kant Shankar, T. Purusothaman · 2009
It is a well accepted verity that the process of data mining produces numerous patterns from the given data. The most significant tasks in data mining are the process of discovering frequent itemsets and association rules. Numerous efficient algorithms are available in the literature for mining frequent itemsets and association rules. Incorporating utility considerations in data mining tasks is gaining popularity in recent years. Certain association rules enhance the business value and the data mining community has acknowledged the mining of these rules of interest since a long time. Several business applications have been found to benefit from the discovery of frequent itemsets and association rules from transaction databases. A comprehensive survey and study of various methods in existence for frequent itemset mining, association rule mining with utility considerations have been presented in this paper.