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Non-negative Matrix Factorization: A Short Survey on Methods and Applications

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Computational Intelligence and Intelligent Systems (ISICA 2012)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 316))

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Abstract

Non-negative matrix factorization (NMF) has been shown to be useful for a variety of practical applications. To meet the requirements of various applications, some extensions of NMF have been proposed as well. This paper presents a short survey on some recent developments of NMF on both the algorithms and applications. Some potential improvements of NMF are also suggested for future study.

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Author information

Authors and Affiliations

  1. Department of Computer Science, East China Normal University, Shanghai, 200235, China

    Zhengyu Huang, Aimin Zhou & Guixu Zhang

Authors
  1. Zhengyu Huang
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  2. Aimin Zhou
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  3. Guixu Zhang
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Editor information

Editors and Affiliations

  1. School of Computer Science, China University of Geosciences, Wuhan, China

    Zhenhua Li  & Xiang Li  & 

  2. School of Computer Science and Engineering, The University of Aizu, Aizu, Japan

    Yong Liu

  3. School of Computer Science, China University of Geosciences, 430074, Wuhan, China

    Zhihua Cai

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Huang, Z., Zhou, A., Zhang, G. (2012). Non-negative Matrix Factorization: A Short Survey on Methods and Applications. In: Li, Z., Li, X., Liu, Y., Cai, Z. (eds) Computational Intelligence and Intelligent Systems. ISICA 2012. Communications in Computer and Information Science, vol 316. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-34289-9_37

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  • DOI: https://doi.org/10.1007/978-3-642-34289-9_37

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-34288-2

  • Online ISBN: 978-3-642-34289-9

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