Non-negative Matrix Factorization, A New Tool for Feature Extraction: Theory and Applications
نویسنده
چکیده
Despite its relative novelty, non-negative matrix factorization (NMF) method knew a huge interest from the scientific community, due to its simplicity and intuitive decomposition. Plenty of applications benefited from it, including image processing (face, medical, etc.), audio data processing or text mining and decomposition. This paper briefly describes the underlaying mathematical NMF theory along with some extensions. Several relevant applications from different scientific areas are also presented. NMF shortcomings and conclusions are considered.
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