关键词: 聚类, 不确定数据, 障碍空间

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.

Key words: clustering, uncertain data, obstacle space