关键词: 模糊C均值, 并行计算, MapReduce编程模型, 数据挖掘, 云计算

Abstract: Fuzzy C-means?is an important?soft-clustering algorithm, but with the increased amount of data the time complexity will be increased. In this paper, a parallel?fuzzy?C-means?algorithm based on?the MapReduce is proposed. The fuzzy?C-means?algorithm is redesigned to meet the MapReduce programming model. The membership degree of data set to the center is computed in parallel, and the new cluster center is re-calculated, so that the higher calculating efficiency of processing large amount of data can be got. The experimental results show that the parallel?fuzzy?C-means?algorithm based on?the MapReduce has the advantages of both high speedup and good scalability.

Key words: fuzzy C-means, parallel computing, MapReduce, data mining, cloud computing