%0 Journal Article
%T A Mathematical Morphology Based Algorithm for Discovering Clusters in Spatial Databases<br>从空间数据库发现聚类：一种基于数学形态学的算法
%A Di Kaichang
%A Li Deren
%A <br>邸凯昌
%A 李德毅
%J 中国图象图形学报
%D 1998
%I 
%X Cluster analysis is an important technique for data mining and knowledge discovery in spatial databases. Its main advantage is the ability to find interesting structures or clusters directly form the spatial data without using any background knowledge. Some available algorithms are reviewed and a mathematical morphology based clustering algorithm (MMC) is presented in this paper. Clusters with arbitrary shape can be discovered by using MMC algorithm, and the optimal cluster number is automatically determined by a heuristic method. The algorithm can be implemented in vector databases as well as in raster databases. The experiments show that the new algorithm is feasible and effective for discovering clusters in spatial databases and is robust when clustering in databases with noise.
%K Clustering algorithm
%K Mathematical morphology
%K Data mining and knowledge discovery
%K Spatial database<br>聚类算法，数学形态学，数据发掘与知识发现，空间数据库
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D06194629680C940ACE75262F54B9D85&aid=1D42C5D63066AF653262D85F0E6E741C&yid=8CAA3A429E3EA654&vid=38B194292C032A66&iid=38B194292C032A66&sid=DABEF202280E7EF1&eid=4609832E4B5C797B&journal_id=1006-8961&journal_name=中国图象图形学报&referenced_num=9&reference_num=11