计算机工程2011，Vol.37Issue(13)：46-48,51,4.DOI:10.3969/j.issn.1000-3428.2011.13.013
基于形态特征的数据流聚类方法研究
Research of Data Stream Clustering Method Based on Shape Feature
摘要
Abstract
In order to retain shape and tend features during the clustering process, this paper proposes a data stream clustering method based on shape feature.In the initialization stage, the subsequence is represented with the important points.In the online update stage, Partial Dynamic Time Warping(PDTW) method is used to compute the distances between the subsequences and ensure the data synchronization using the dynamic sliding window.In the clustering stage triggered by the user, the data streams clustering method is proposed.Experimental results show that the shape-based clustering over data streams can get the evolution accuracy of 0.95 with the reasonable parameters.关键词
数据流/聚类演化/数据挖掘/形态特征Key words
data stream/ clustering evolution/ data mining/ shape feature分类
信息技术与安全科学引用本文复制引用
吴学雁,黄道平..基于形态特征的数据流聚类方法研究[J].计算机工程,2011,37(13):46-48,51,4.基金项目
广东省自然科学基金资助项目(6300278) （6300278）
广东工业大学青年基金资助项目(092036) （092036）
