A comparative analysis on efficiency of contemporary association rule mining algorithm

A vital procedure that is indispensable in the field of data mining is the association rule mining in which the focus is up on the finding of the curious associations, correlations and frequent item sets amongst the list of items in a given database. There are typically two steps in the algorithms that employ association rules. The first step being the finding of the frequent sets and the second being the usage of these sets in order to generate the association rules. The current paper puts forward an analysis of comparison between the various association rule mining algorithms. Besides, the applications, benefits and the drawbacks have also been studied in the paper. The paper reviews the features, data sets variants, support, confidence, rule generation and candidate generation of the algorithms that are employed to mine the association rules.