Abstract
ABSTRACT As BigData is issued, many applications that operate based on t he results of data analysis have been developed, typically applications are products recommend service of e-commerce appli cation service system, search service on the search engine serv ice and friend list recommend system of social network service.In this paper, we suggests a decision frequent pattern tree tha t is combined the origin frequent pattern tree that is mining s imilar pattern to appear in the data set of the existing data mining t echniques and decision tree based on the theory of computer sci ence. The decision frequent pattern tree algorithm improves about pro blem of frequent pattern tree that have to make some a lot’s pattern so it is to hard to analyze about data. We also proposes to mod el for a Mapredue framework that is a programming model to help to operate in distributed environment. ☞ keyword : SData Mining, Frequent-Pattern tree, Clustering Algor ithms, Distributed Processing System, Recommendation System, Map Reduce
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