The rise of nonnegative matrix factorization: Algorithms and applications

• Published in: Information systems (Oxford) Vol. 123; p. 102379
• Main Authors: Guo, Yi-Ting, Li, Qin-Qin, Liang, Chun-Sheng
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.07.2024
• Subjects: Algorithms; Applications; Case-by-case NMF; Dynamic NMF; NMF computing procedures; NMF features; NMF mathematical principles; NMF performance; Nonnegative matrix factorization; Programming languages; Reinforcement learning; Self-correction NMF; Supervised learning; Dynamic NMF; Applications; Nonnegative matrix factorization; Case-by-case NMF; Reinforcement learning; NMF mathematical principles; NMF performance; Programming languages; NMF features; Algorithms; Supervised learning; Self-correction NMF; NMF computing procedures
• ISSN: 0306-4379; 1873-6076
• DOI: 10.1016/j.is.2024.102379

•NMF has been applied in about 130 fields (disciplines) in recent years.•The use of NMF in programming languages (free platforms) is summarized.•The classical basic NMF optimization methods are used in many NMF algorithms.•Supervised learning and reinforcement learning are gradually included in NMF....