• Journal of Internet Computing and Services
    ISSN 2287 - 1136(Online) / ISSN 1598 - 0170 (Print)
    http://jics.or.kr/

Clustering Algorithm using the DFP-Tree based on the MapReduce


Young-Won Seo, Chang-soo Kim, Journal of Internet Computing and Services, Vol. 16, No. 6, pp. 23-30, Dec. 2015
10.7472/jksii.2015.16.6.23, Full Text:
Keywords: SData Mining, Frequent-Pattern tree, Clustering Algorithms, Distributed Processing System, Recommendation System, Map Reduce

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.


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Cite this article
[APA Style]
Young-Won Seo and Chang-soo Kim (2015). Clustering Algorithm using the DFP-Tree based on the MapReduce. Journal of Internet Computing and Services, 16(6), 23-30. DOI: 10.7472/jksii.2015.16.6.23.

[IEEE Style]
Y. Seo and C. Kim, "Clustering Algorithm using the DFP-Tree based on the MapReduce," Journal of Internet Computing and Services, vol. 16, no. 6, pp. 23-30, 2015. DOI: 10.7472/jksii.2015.16.6.23.

[ACM Style]
Young-Won Seo and Chang-soo Kim. 2015. Clustering Algorithm using the DFP-Tree based on the MapReduce. Journal of Internet Computing and Services, 16, 6, (2015), 23-30. DOI: 10.7472/jksii.2015.16.6.23.