摘要
目前大多数聚类算法主要针对空间点对象且未考虑空间对象的拓扑关系。利用空间线对象相交关系定义了空间线对象连接度,提出一种基于连接度的空间线对象聚类算法SLCC(Spatial Lines Clustering Algorithm Based on Connectivity)。该算法以K-means算法为基础,以空间线对象的连接度作为"距离"进行空间线对象聚类。实验结果表明,SLCC算法能实现空间线对象的空间聚类,并具有较高的效率。
At present,most spatial clustering algorithms focus on spatial points without considering spatial topological relations of spatial objects.The spatial line connectivity was defined by line intersection relations.Algorithm SLCC was proposed for clustering spatial lines based on spatial line connectivity.This algorithm,which is based on K-means,selects the spatial line connectivity as the distance between lines to cluster spatial lines.The experiment results show the algorithm is effective and efficient.
出处
《计算机科学》
CSCD
北大核心
2011年第8期179-181,204,共4页
Computer Science
基金
国家自然科学基金(40871176)资助
关键词
连接度
空间聚类
拓扑关系
线相交
Spatial line connectivity
Spatial clustering
Topological relations
Line intersection