Literature Review on Infrequent Itemset Mining Algorithms

The aim of association rule mining is to find the correlation between data Items based on frequency of occurrence. Infrequent Itemset mining is a variation of frequent itemset mining where it finds the uninteresting patterns i.e., it finds the data items which occurs very rarely. Considering weight for each distinct items in a transaction independent manner adds effectiveness for finding frequent itemset mining. Several articles related to frequent and weighted infrequent itemset mining were proposed. This paper focus on reviewing various existing algorithms related to frequent and infrequent itemset mining which creates a path for future researches in the field of association rule mining.

Provided by: International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE) Topic: Data Management Date Added: Aug 2014 Format: PDF

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