关键词: 数据流, 聚类, 滑动窗口, 微簇, 界标模型

Abstract: Stream data clustering algorithm was improved in terms of cluster quality and efficiency. This paper adopted a new method to improve cluster quality and efficiency. Firstly, the technology of the time-based sliding window was applied. Secondly, the structure of improved micro-cluster was created to save the summary. Finally, a new strategy was designed to regularly delete expired micro-clusters and outlier micro-clusters. Compared with traditional clustering algorithms of landmark-based model, the proposed method is of better efficiency, less memory overhead and fast data processing capabilities.

Key words: data stream, clustering, sliding window, micro cluster, landmark model