An Effective Initialization for Orthogonal Nonnegative Matrix Factorization

An Effective Initialization for Orthogonal Nonnegative Matrix Factorization

Year:    2012

Journal of Computational Mathematics, Vol. 30 (2012), Iss. 1 : pp. 34–46

Abstract

The orthogonal nonnegative matrix factorization (ONMF) has many applications in a variety of areas such as data mining, information processing and pattern recognition. In this paper, we propose a novel initialization method for the ONMF based on the Lanczos bidiagonalization and the nonnegative approximation of rank one matrix. Numerical experiments are given to show that our initialization strategy is effective and efficient.

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Journal Article Details

Publisher Name:    Global Science Press

Language:    English

DOI:    https://doi.org/10.4208/jcm.1110-m11si10

Journal of Computational Mathematics, Vol. 30 (2012), Iss. 1 : pp. 34–46

Published online:    2012-01

AMS Subject Headings:   

Copyright:    COPYRIGHT: © Global Science Press

Pages:    13

Keywords:    Lanczos bidiagonalization Orthogonal nonnegative matrix factorization Low-rank approximation Nonnegative approximation.

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