%0 Journal Article
%T Clustering algorithm based on attribute-relationship integrated similarity<br>基于属性—关系综合相似度的聚类算法*
%A WU Ling-yu
%A GAO Xue-dong
%A WU Sen
%A <br>吴玲玉
%A 高学东
%A 武森
%J 计算机应用研究
%D 2011
%I 
%X In order to improve the attribute space clustering methods that focus on the attribute information only,and improve the structure clustering methods that focus on relationship only,this paper proposed a clustering algorithm based on attribute-relationship integrated similarity.After setting up the weighted network based on attribute distance, the algorithm showed how to calculate the integrated similarity between objects and between clusters, and provided appropriate strategy to aggregating clusters from bottom up. In comparison with attribute space clustering methods and structure clustering methods, the algorithm has higher accuracy for considering more information. In comparison with classic method based on attribute-relationship similarity like HyPursuit or M-S, the algorithm has better efficiency for simplifying the computing process of integrated similarity.
%K data mining
%K clustering
%K weighted network based on attribute distance
%K integrated similarity<br>数据挖掘
%K 聚类
%K 基于属性距离的有权网络
%K 综合相似度
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=219CA7FFE15D09DC4D1503FF7CF98546&yid=9377ED8094509821&vid=D3E34374A0D77D7F&iid=CA4FD0336C81A37A&sid=1AE5323881A5ECDC&eid=F4B561950EE1D31A&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=17