文章基本信息

标题：Reduction of Online Execution Time for Big Data Application
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作者：P.S.Manikandan ; M.Vimalan ; Prof K.Ravikumar 等
期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2015
卷号：3
期号：5
DOI：10.15680/ijircce.2015.0305154
出版社：S&S Publications
摘要：An increasing number of services are emerging on the Internetby service computing and cloudcomputing. As a result, service-relevant data become too big to be effectively processed by traditional approaches. Inview of this challenge, Reduction of online execution time for big data application is proposed in this paper, whichaims at recruiting similar services in the same clusters to recommend services collaboratively. Technically, thisapproach is enacted around two stages. In the first stage, the available services are divided into small-scale clusters, inlogic, for further processing. At the second stage, a collaborative filtering algorithm is imposed on one of the clusters.Since the number of the services in a cluster is much less than the total number of the services available on the web, itis expected to reduce the online execution time of collaborative filtering. At last, several experiments are conducted toverify the availability of the approach.
关键词：big data application; cluster; collaborative filtering; mash up