期刊名称：International Journal of Grid and Distributed Computing
印刷版ISSN：2005-4262
出版年度：2015
卷号：8
期号：3
页码：43-52
DOI：10.14257/ijgdc.2015.8.3.05
出版社：SERSC
摘要：It is an importance step for near-duplication detection to perform file classification in the data mining field, in this paper an improved classification course is proposed which consists of training and test course corresponding to its algorithm respectively. It utilizes the MapReduce computing model created by Google to conduct the classification calculation. Specially, the Sogou news data with various data amounts which simulated the massive data set was used for testing effectiveness and a comparative evaluation on execution time and speedup was accomplished on the experimental circumstance. The results obtained shows that the classification course obviously reduces the execution times greatly and gains the ideal speedup ratio when increasing data amounts, achieves the better performance.
关键词：Classification; Na.ve Byes; Algorithm; MapReduce; Massive Data
