In this paper, we propose a novel document clustering method based on the non-negative factorization of the termdocument matrix of the given document corpus. In the latent semanti...
Non-negative Matrix Factorization (NMF, [5]) and Probabilistic Latent Semantic Analysis (PLSA, [4]) have been successfully applied to a number of text analysis tasks such as docum...
Non-negative matrix factorization (NMF) is a recently developed method for finding parts-based representation of non-negative data such as face images. Although it has successfully...
In this paper, a new approach for automatic audio classification using non-negative matrix factorization (NMF) is presented. Training is performed onto each audio class individua...
— Non-negative Matrix factorization (NMF) has increasingly been used as a tool in signal processing in the last couple of years. NMF, like independent component analysis (ICA) is...
In this study Principal Component Analysis (PCA), Non-negative Matrix Factorization (NMF) and Nonnegative Tensor Factorization (NTF) are applied as dimension reduction methods in ...
Alexey Andriyashin, Jussi Parkkinen, Timo Jaaskela...
Recently Non-negative Matrix Factorization (NMF) has received a lot of attentions in information retrieval, computer vision and pattern recognition. NMF aims to find two non-nega...
In this paper, we present an efficient system for action recognition from very short sequences. For action recognition typically appearance and/or motion information of an action ...
—It is a fact that vast majority of attention is given to protecting against external threats, which are considered more dangerous. However, some industrial surveys have indicate...
The blogosphere has unique structural and temporal properties since blogs are typically used as communication media among human individuals. In this paper, we propose a novel tech...