Abstract
A social networking site such as Facebook, Twitter, and Linked In generates a terabyte of data. The Frequent Itemset Mining (FIM) is most well known technique to extract knowledge from data. Mining terabytes of data using Frequent Itemset Mining technique on a single computer is not efficient. MapReduce framework is used for mining such large data in a parallel manner. MRApriori, IMRApriori, BigFIM, ClustBigFIM, MREclat are used for Frequent Itemset Mining with MapReduce framework. In this paper we have discussed different Frequent Itemset mining algorithms with MapReduce framework and compared in terms of scalability, speedup and execution time.
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