计算机工程Issue(12)：188-194,7.DOI:10.3969/j.issn.1000-3428.2014.12.035
基于扩展网格和密度的数据流聚类算法
Data Stream Clustering Algorithm Based on Extensible Grid and Density
邢长征 1王晓旭1
作者信息
- 1. 辽宁工程技术大学电子与信息工程学院，辽宁 葫芦岛125105
- 折叠
摘要
Abstract
With regard to the previous phenomenon,when traditional clustering algorithms compute grid density without considering the surrounding space which leads to the unsmoothed clustering,this paper presents a data stream clustering algorithm based on extensible grid and density. By dynamically determining the grid expansion area, the algorithm reasonably expands the calculation range of grid density from this grid to the adjacent ones, and then according to the cohesion degree which is introduced from algorithm to measure the impact of surrounding data on grid density. In order to further outline the distribution of the clustering edges, the algorithm uses the boundary threshold value method which separates the boundary points from the noise. Furthermore, the algorithm puts forward an improved grid combining method which is on the basis of the judgment of inter-cluster connectivity to simplify the combination of grid clusters,and this effectively reduces the execution time of the algorithm. Experimental results show that the algorithm has higher clustering quality and efficiency.关键词
聚类/扩展网格/网格密度/凝聚度/连通性/边界点Key words
clustering/extensible grid/grid density/cohesion degree/connectivity/boundary point分类
信息技术与安全科学引用本文复制引用
邢长征,王晓旭..基于扩展网格和密度的数据流聚类算法[J].计算机工程,2014,(12):188-194,7.
