Volume 30, Issue 1
An Effective Initialization for Orthogonal Nonnegative Matrix Factorization

Xuansheng Wang, Xiaoyao Xie & Linzhang Lu

DOI: 10.4208/jcm.1110-m11si10

J. Comp. Math., 30 (2012), pp. 34-46

Published online: 2012-02

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  • 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.

  • Keywords

Lanczos bidiagonalization Orthogonal nonnegative matrix factorization Low-rank approximation Nonnegative approximation

  • AMS Subject Headings

65F99.

  • Copyright

COPYRIGHT: © Global Science Press

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@Article{JCM-30-34, author = {Xuansheng Wang, Xiaoyao Xie and Linzhang Lu}, title = {An Effective Initialization for Orthogonal Nonnegative Matrix Factorization}, journal = {Journal of Computational Mathematics}, year = {2012}, volume = {30}, number = {1}, pages = {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.}, issn = {1991-7139}, doi = {https://doi.org/10.4208/jcm.1110-m11si10}, url = {http://global-sci.org/intro/article_detail/jcm/8415.html} }
TY - JOUR T1 - An Effective Initialization for Orthogonal Nonnegative Matrix Factorization AU - Xuansheng Wang, Xiaoyao Xie & Linzhang Lu JO - Journal of Computational Mathematics VL - 1 SP - 34 EP - 46 PY - 2012 DA - 2012/02 SN - 30 DO - http://doi.org/10.4208/jcm.1110-m11si10 UR - https://global-sci.org/intro/article_detail/jcm/8415.html KW - Lanczos bidiagonalization KW - Orthogonal nonnegative matrix factorization KW - Low-rank approximation KW - Nonnegative approximation AB - 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.
Xuansheng Wang, Xiaoyao Xie & Linzhang Lu. (1970). An Effective Initialization for Orthogonal Nonnegative Matrix Factorization. Journal of Computational Mathematics. 30 (1). 34-46. doi:10.4208/jcm.1110-m11si10
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