Non-negative matrix factorization (NMF) is the problem of determining two non-negative low rank factors W and H, for the given input matrix A, such that A approximate to WH. NMF is a useful tool for many applications in di ff erent domains such as topic modeling in text mining, background separation in video analysis, and community detection in social networks. Despite its popularity in the data mining community, there is a lack of e ffi cient distributed algorithms to solve the problem for big data sets.
展开▼
