计算机应用 ›› 2010, Vol. 30 ›› Issue (4): 1093-1095.

• 数据库与数据挖掘 • 上一篇    下一篇

滑动窗口内基于密度网格的数据流聚类算法

李子文1,邢长征2   

  1. 1. 辽宁工程技术大学
    2.
  • 收稿日期:2009-11-06 修回日期:2009-12-08 发布日期:2010-04-15 出版日期:2010-04-01
  • 通讯作者: 李子文

Density grid-based data stream clustering algorithm over sliding window

  • Received:2009-11-06 Revised:2009-12-08 Online:2010-04-15 Published:2010-04-01

摘要: 提出了一种基于密度网格的数据流聚类算法。通过引入“隶度”,对传统的基于网格密度的数据流聚类算法,以网格内数据点的个数作为网格密度的思想加以改进,解决了一个网格内属于两个类的数据点以及边界点的处理问题。从而既利用了基于网格算法的高效率,还较大程度地提高了聚类精度。

关键词: 聚类, 数据流, 网格, 滑动窗口, 隶度

Abstract: This paper introduced a density grid-based data stream clustering algorithm. Through the introduction of the "subject degree", the traditional density grid-based clustering algorithm for data stream was improved by taking the data points within the grid as the grid density, thereby resolving the problem of data points belonging to two classes in one grid as well as the treatment of boundary points. Therefore, not only the high efficiency of the grid-based algorithm was utilized, but also the clustering accuracy was raised significantly.

Key words: clustering, data stream, grid, sliding window, subject degree