计算机应用研究2013，Vol.30Issue(4)：1015-1016,1034,3.DOI:10.3969/j.issn.1001-3695.2013.04.014
一种基于图论的加权聚类融合算法
Weighted cluster fusion algorithm based on graph
摘要
Abstract
The results of the existing cluster fusion algorithms are usually not so good when they process the mixed attributes datas, the main reason is that the results of the algorithms are still dispersed. To solve this problem, this paper presented a new weighted cluster fusion algorithm based on graph theory. It first clustered the datasets and got cluster members, and then set weights to each data object with a proposed fusion function, and determined the relationship between the data-pair by setting weights to the edges between them, so it could get a weighted nearest neighbor graph. At last it did a last-clustering based on graph theory. Experiments show that the accuracy and stability of this cluster fusion algorithm is better than other clustering fusion algorithms.关键词
聚类融合/融合函数/混合属性/图论/加权Key words
cluster fusion/ fusing function/ mixed attributes/ graph theory/ weighted分类
信息技术与安全科学引用本文复制引用
谢岳山,樊晓平,廖志芳,尹红练,罗浩..一种基于图论的加权聚类融合算法[J].计算机应用研究,2013,30(4):1015-1016,1034,3.基金项目
国家科技支撑项目计划资助项目(2012BAH08B01) （2012BAH08B01）
湖南省自然科学基金资助项目(12JJ3074) （12JJ3074）
