A matrix factorization framework for jointly analyzing multiple nonnegative data
Nonnegative matrix factorization based methods provide one of the simplest and most effective approaches to text mining. However, their applicability is mainly limited to analyzing a single data source. In this paper, we propose a novel joint matrix factorization framework which can jointly analyze...
| Main Authors: | , , , |
|---|---|
| Other Authors: | |
| Format: | Conference Paper |
| Published: |
Omnipress
2011
|
| Online Access: | http://hdl.handle.net/20.500.11937/16617 |