reviewIEEE Transactions on Knowledge and Data EngineeringMar 6, 2012Closed access

Nonnegative Matrix Factorization: A Comprehensive Review

Tsinghua University

Indexed incrossref

Abstract

Nonnegative Matrix Factorization (NMF), a relatively novel paradigm for dimensionality reduction, has been in the ascendant since its inception. It incorporates the nonnegativity constraint and thus obtains the parts-based representation as well as enhancing the interpretability of the issue correspondingly. This survey paper mainly focuses on the theoretical research into NMF over the last 5 years, where the principles, basic models, properties, and algorithms of NMF along with its various modifications, extensions, and generalizations are summarized systematically. The existing NMF algorithms are divided into four categories: Basic NMF (BNMF), Constrained NMF (CNMF), Structured NMF (SNMF), and Generalized…

Citation impact

987
total citations
FWCI
24.41
Percentile
100%
References
165
Citations per year

Authors

2

Topics & keywords

Keywords
  • Non-negative matrix factorization
  • Interpretability
  • Computer science
  • Curse of dimensionality
  • Matrix decomposition
  • Constraint (computer-aided design)
  • Dimensionality reduction
  • Artificial intelligence
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