An extension of PLSA for document clustering

In this paper we propose an extension of the PLSA model in which an extra latent variable allows the model to cocluster documents and terms simultaneously. We show on three datasets that our extended model produces statistically significant improvements with respect to two clustering measures over the original PLSA and the multinomial mixture MM models. Categories and Subject Descriptors H.3.3 [Information search and Retrieval]: Clustering; I.5.3 [Clustering]: Algorithms General Terms Algorithms, Experimentation Keywords Document Clustering, PLSA

• Type: Conference
• Year: 2008
• Where: CIKM
• Authors: Young-Min Kim, Jean-François Pessiot, Massih-Reza Amini, Patrick Gallinari
• Keywords: Algorithms General Terms, CIKM 2008, Document Clustering, Information Management, Multinomial Mixture Mm