摘要
在空间数据挖掘中,传统聚类算法忽略了真实世界中障碍物的存在,而障碍物会影响聚类结果的合理性。讨论了面对障碍物的聚类问题,并给出了一个考虑障碍物存在时的基于划分的聚类算法。该算法充分考虑到了现实障碍物对聚类结果的影响,使得聚类结果更具有实际意义。
In spatial data mining, classic algorithms about clustering have ignored the fact that physical obstacles exist in the real world and could affect the correctness about clustering results . This paper discussed the problem of clustering in the presence of obstacles and presents an algorithm for it. The algorithm considered obstacles to make the clustering results more practical.'
出处
《计算机应用》
CSCD
北大核心
2003年第12期73-75,共3页
journal of Computer Applications
关键词
空间数据挖掘
聚类
距离函数
spatial data mining
clustering
distance function
