面向科技管理的流数据聚类算法研究

介绍了科学管理流数据的流数据管理系统及根据BIRCH算法中聚类特征的概念,利用簇特征设计与实现了一种新的动态流数据聚类算法。这种新算法改善了基于滑动窗口流数据聚类的有效性以及空间和时间复杂度问题。理论分析和实验结果证明该算法能够有效地处理滑动窗口流数据集,使聚类算法具有良好的可扩展性。

Research on Clustering Algorithm Based on Cluster Feature in Data Stream Management

This article first introduce the data stream management system with managing the data stream scientific management and then introduce the notion of clustering feature of BIRCH,a dynamic data stream clustering algorithm is designed and implemented,which solves the problems of effectiveness,space and time complexities of clustering algorithms for large databases.Theoretic analysis and experimental results demonstrate that the dynamic clustering algorithm can not only handle sliding windows datasets,but also has good scalability.