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http://dx.doi.org/10.7472/jksii.2015.16.6.23

Clustering Algorithm using the DFP-Tree based on the MapReduce  

Seo, Young-Won (Department of IT Convergence and Application Engineering, Pukyong National University)
Kim, Chang-soo (Department of IT Convergence and Application Engineering, Pukyong National University)
Publication Information
Journal of Internet Computing and Services / v.16, no.6, 2015 , pp. 23-30 More about this Journal
Abstract
As BigData is issued, many applications that operate based on the results of data analysis have been developed, typically applications are products recommend service of e-commerce application service system, search service on the search engine service and friend list recommend system of social network service. In this paper, we suggests a decision frequent pattern tree that is combined the origin frequent pattern tree that is mining similar pattern to appear in the data set of the existing data mining techniques and decision tree based on the theory of computer science. The decision frequent pattern tree algorithm improves about problem 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 model for a Mapredue framework that is a programming model to help to operate in distributed environment.
Keywords
SData Mining; Frequent-Pattern tree; Clustering Algorithms; Distributed Processing System; Recommendation System; Map Reduce;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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