Feature subset non-negative matrix factorization and its applications to document understanding

Authors:
Dingding Wang;Chris Ding;Tao Li
Affiliations:
Florida International University, Miami, FL, USA;University of Texas at Arlington, Arlington, TX, USA;Florida International University, Miami, FL, USA
Venue:
Proceedings of the 33rd international ACM SIGIR conference on Research and development in information retrieval
Year:
2010

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Abstract

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.