<cite>Weighted Textual Matrix Factorization [WTMF]</cite> (<cite>Guo and Diab, 2012b</cite> ) is a latent variable model that outperforms Latent Semantic Analysis [LSA] (Deerwester et al., 1990) and Latent Dirichelet Allocation [LDA] (Blei et al., 2003) models by a large margin in the SS task, yielding state-of-the-art performance on the LI06 (Li et al., 2006 ) SS dataset.