%0 Journal Article
%T Research on Cluster Aggregation Approaches<br>聚类集成方法研究
%A YANG Cao-yuan
%A LIU Da-you
%A YANG Bo
%A CHI Shu-zhen
%A JIN Di
%A <br>杨草原
%A 刘大有
%A 杨博
%A 池淑珍
%A 金弟
%J 计算机科学
%D 2011
%I 
%X Clustering aggregation can offer a partition that could better reflect the inherent structure of the data set by studying and integrating many clustering results of the original data set. Clustering aggregation could detect and deal with the isolated points preferably, which improves the quality of clustering. This paper made an overview of the relevant knowledge of the clustering aggregation, presented the concepts and advantages of clustering aggregation. It presented three approaches to get clustering members according to the ucsd cluster algorithms; analysed their respective advantages, disadvantages and application conditions; presented the existing consensus functions; explained the basic principles and pointed out their limitations. Finally, it discussed the future research directions.
%K Clustering aggregation
%K Clustering member
%K Consensus function
%K Clustering algorithms<br>聚类集成，聚类成员，一致性函数，聚类算法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=6EC07AB3B3D0AF9F7BC8E1AD811E5ABF&yid=9377ED8094509821&vid=16D8618C6164A3ED&iid=0B39A22176CE99FB&sid=43608FD2E15CD61B&eid=C5F8B8CB20F1B3D8&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=32