Efficient Document Clustering via Online Nonnegative Matrix Factorizations [chapter]

Fei Wang, Chenhao Tan, Ping Li, Arnd Christian König
2011 Proceedings of the 2011 SIAM International Conference on Data Mining  
In recent years, Nonnegative Matrix Factorization (NMF) has received considerable interest from the data mining and information retrieval fields. NMF has been successfully applied in document clustering, image representation, and other domains. This study proposes an online NMF (ONMF) algorithm to efficiently handle very large-scale and/or streaming datasets. Unlike conventional NMF solutions which require the entire data matrix to reside in the memory, our ONMF algorithm proceeds with one data
more » ... ceeds with one data point or one chunk of data points at a time. Experiments with one-pass and multi-pass ONMF on real datasets are presented.
doi:10.1137/1.9781611972818.78 dblp:conf/sdm/WangLK11 fatcat:myhxbzaevrddbhari6igldfqma