Feature subset non-negative matrix factorization and its applications to document understanding
Dingding Wang, Chris H. Q. Ding, Tao Li · 2010
In this paper, we propose feature subset non-negative matrix factorization (NMF), which is an unsupervised approach to simultaneously cluster data points and select important features. We apply our proposed approach to various document understanding tasks including document clustering, summarization, and visualization. Experimental results demonstrate the effectiveness of our approach for these tasks.