International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 46 - Number 23 |
Year of Publication: 2012 |
Authors: Endu Duneja, A.k. Sachan |
10.5120/7105-9720 |
Endu Duneja, A.k. Sachan . A Survey on Frequent Itemset Mining with Association Rules. International Journal of Computer Applications. 46, 23 ( May 2012), 18-24. DOI=10.5120/7105-9720
Data mining techniques comprises of Clustering, Association, Sequential mining, Classification, Regression and Deviation detection Association Rule mining is one of the utmost ubiquitous data mining techniques which can be defined as extracting the interesting correlation and relation among huge amount of transactions. Many applications engender colossal amount of operational and behavioral data. Copious effective algorithms are proposed in the literature for mining frequent itemsets and association rules. Integrating efficacy considerations in data mining tasks is reaping popularity in recent years. Business value is enhanced by certain association rules and the data mining community has acknowledged the mining of these rules of interest since a long time. The discovery of frequent itemsets and association rules from transaction databases has aided many business applications. To discover the concealed knowledge from these data association rule mining can be applied in any application. A comprehensive analysis, survey and study of various approaches in existence for frequent itemset extraction, association rule mining with efficacy contemplations have been presented in this paper.