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Relationship Matrix Nonnegative Decomposition for Clustering
Joint Authors
Source
Mathematical Problems in Engineering
Issue
Vol. 2011, Issue 2011 (31 Dec. 2011), pp.1-15, 15 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2011-05-05
Country of Publication
Egypt
No. of Pages
15
Main Subjects
Abstract EN
Nonnegative matrix factorization (NMF) is a popular tool for analyzing the latent structure of nonnegative data.
For a positive pairwise similarity matrix, symmetric NMF (SNMF) and weighted NMF (WNMF) can be used to cluster the data.
However, both of them are not very efficient for the ill-structured pairwise similarity matrix.
In this paper, a novel model, called relationship matrix nonnegative decomposition (RMND), is proposed to discover the latent clustering structure from the pairwise similarity matrix.
The RMND model is derived from the nonlinear NMF algorithm.
RMND decomposes a pairwise similarity matrix into a product of three low rank nonnegative matrices.
The pairwise similarity matrix is represented as a transformation of a positive semidefinite matrix which pops out the latent clustering structure.
We develop a learning procedure based on multiplicative update rules and steepest descent method to calculate the nonnegative solution of RMND.
Experimental results in four different databases show that the proposed RMND approach achieves higher clustering accuracy.
American Psychological Association (APA)
Pan, Ji-Yuan& Zhang, Jiang-She. 2011. Relationship Matrix Nonnegative Decomposition for Clustering. Mathematical Problems in Engineering،Vol. 2011, no. 2011, pp.1-15.
https://search.emarefa.net/detail/BIM-504487
Modern Language Association (MLA)
Pan, Ji-Yuan& Zhang, Jiang-She. Relationship Matrix Nonnegative Decomposition for Clustering. Mathematical Problems in Engineering No. 2011 (2011), pp.1-15.
https://search.emarefa.net/detail/BIM-504487
American Medical Association (AMA)
Pan, Ji-Yuan& Zhang, Jiang-She. Relationship Matrix Nonnegative Decomposition for Clustering. Mathematical Problems in Engineering. 2011. Vol. 2011, no. 2011, pp.1-15.
https://search.emarefa.net/detail/BIM-504487
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-504487