Random Projection Based Clustering Method of Parallel Data Streams
CHEN Hua-Hui1,2, SHI Bo-Le1
1.Department of Computing and Information Technology, Fudan University, Shanghai 200433 2.School of Information Science and Engineering, Ningbo University, Ningbo 315211
Abstract：A synopsis is maintained dynamically for each data stream. The construction of the synopsis is based on random projections and it utilizes the amnesic feature of data stream. Using the synopsis, the approximate distances between streams and the cluster center can be computed fast. And an efficient online version of the classical K-means clustering algorithm is developed. The experimental results show the method can be performed effectively with a good clustering quality.
陈华辉，施伯乐. 基于随机投影的并行数据流聚类方法*[J]. 模式识别与人工智能, 2009, 22(1): 113-122.
CHEN Hua-Hui, SHI Bo-Le. Random Projection Based Clustering Method of Parallel Data Streams. , 2009, 22(1): 113-122.
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