Extended Semi-supervised Matrix Factorization for Clustering

摘要：

In this paper, we extend the Penalized Matrix Factorization (PMF) algorithm for semi-supervised clustering. The definition of may-link constraints are introduced and obtained based on must-link constraints and cluster structure. We derive the Extended PMF (EPMF) model by incorporating the may-link constraints inside the original PMF decomposition. Extensive experimental evaluations are performed on the SECTOR data set. The experimental results show the effectiveness of the extended PMF.

关键词： Nonnegative matrix factorization Penalized matrix factorization Semi-supervised clustering

作者: Pei Xiaobing Fang Shaohong Chen Chuanbo

作者单位: School of Software, HuaZhong University of Science & Technology Wuhan, Hubei 430074, China

会议类型: 国际会议

会议名称: 2010 International Conference on Intelligent Computation Technology and Automation(2010 智能计算技术与自动化国际会议 ICICTA 2010)

会议地点: 长沙

会议语种:英文

页码: 1451-1454

在线出版日期: 2010-05-11（万方平台首次上网日期，不代表论文的发表时间）