Locally Consistent Concept Factorization for Document Clustering

—Previous studies have demonstrated that document clustering performance can be improved significantly in lower dimensional linear subspaces. Recently, matrix factorization based techniques, such as Non-negative Matrix Factorization (NMF) and Concept Factorization (CF), have yielded impressive results. However, both of them effectively see only the global Euclidean geometry, whereas the local manifold geometry is not fully considered. In this paper, we propose a new approach to extract the document concepts which are consistent with the manifold geometry such that each concept corresponds to a connected component. Central to our approach is a graph model which captures the local geometry of the document submanifold. Thus we call it Locally Consistent Concept Factoriaztion (LCCF). By using the graph Laplacian to smooth the document-to-concept mapping, LCCF can extract concepts with respect to the intrinsic manifold structure and thus documents associated with the same concept can be ...

• Type: Journal
• Year: 2011
• Where: TKDE
• Authors: Deng Cai, Xiaofei He, Jiawei Han
• Keywords: Documents, Manifold Geometry, Non-Negative Matrix Factorization, TKDE 2011