Optimal algorithm of data streams clustering on sliding window model
滑动窗口模型下的优化数据流聚类算法

Streaming data clustering algorithm was improved based on sliding window model with the purpose of high cluster quality and efficiency. The new algorithm adopted cluster feature histograms as the data supporting structure. Compared with traditional cluster algorithms, the complexity and clustering effect of new algorithm was further improved. In addition, the algorithm is of better efficiency, less memory overhead and fast data processing capabilities, and the application of data streaming mining technologies is expanded.