计算机科学与探索2012，Vol.6Issue(12)：1087-1097,11.DOI:10.3778/j.issn.1673-9418.2012.12.003
障碍空间中不确定数据聚类算法
Clustering Algorithm of Uncertain Data in Obstacle Space
摘要
Abstract
In recent years, uncertain data is generated widely in location data due to the inaccuracy of measurement instruction or the data attributes itself. The existence of obstacles in space brings the new challenges to spatial uncertain data clustering. This paper proposes OBS-UK-means (obstacle uncertain K-means) algorithm to cluster uncertain data in obstacle space, and also proposes two pruning strategies based on R-tree and Voronoi diagram and the shortest distance area concept, that greatly reduces the calculations. Finally, the experiment demonstrates that the efficiency and accuracy of the OBS-UK-means algorithm, and the pruning approach can improve the efficiency of the clustering algorithm, meanwhile, it doesn' t damage the cluster effectiveness.关键词
聚类/不确定数据/障碍空间Key words
clustering/ uncertain data/ obstacle space分类
信息技术与安全科学引用本文复制引用
曹科研,王国仁,韩东红,袁野,胡雅超,齐宝雷..障碍空间中不确定数据聚类算法[J].计算机科学与探索,2012,6(12):1087-1097,11.基金项目
The National Natural Science Foundation of China under Grant Nos.61025007,60933001,61100024,61173029(国家自然科学基金) （国家自然科学基金）
the Fundamental Research Funds for the Central Universities of China under Grant No.N110404011(中央高校基本科研业务费专项资金). （中央高校基本科研业务费专项资金）
