Title :
Extended Semi-supervised Matrix Factorization for Clustering
Author :
Xiaobing, Pei ; Shaohong, Fang ; Chuanbo, Chen
Author_Institution :
Sch. of Software, HuaZhong Univ. of Sci. & Technol., Wuhan, China
Abstract :
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.
Keywords :
learning (artificial intelligence); matrix decomposition; pattern clustering; extended semisupervised matrix factorization; matrix decomposition; penalized matrix factorization; semisupervised clustering; Automation; Clustering algorithms; Data mining; Digital images; Machine learning; Matrix decomposition; Performance evaluation; Software algorithms; Nonnegative matrix factorization; Penalized matrix factorization; Semi-supervised clustering;
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4244-7279-6
Electronic_ISBN :
978-1-4244-7280-2
DOI :
10.1109/ICICTA.2010.544
