Posterior probabilistic clustering using NMF

We introduce the posterior probabilistic clustering (PPC), which provides a rigorous posterior probability interpretation for Nonnegative Matrix Factorization (NMF) and removes the uncertainty in clustering assignment. Furthermore, PPC is closely related to probabilistic latent semantic indexing (PLSI). Categories and Subject Descriptors H.3.3 [Information Search and Retrieval]: Clustering; I.2 [Artificial Intelligence]: Learning General Terms Algorithms, Experimentation, Measurement, Performance, Theory Keywords Sparse, Posterior Probabilistic Clustering, NMF

• Type: Journal
• Year: 2008
• Where: SIGIR
• Authors: Chris H. Q. Ding, Tao Li, Dijun Luo, Wei Peng
• Keywords: Information Technology, Nonnegative Matrix Factorization, Posterior Probabilistic Clustering, Rigorous Posterior Probability, SIGIR 2008