Statistical methods to modeling language semantics have proven to deliver good results in many natural language processing applications.
probabilistic topic models have been successfully used for tasks such as summarization (Gong and Liu, 2001;Hennig, 2009), text segmentation (Misra et al., 2009), lexical substitution (Dinu and Lapata, 2010) or word sense disambiguation (Cai et al., 2007;Boyd-Graber et al., 2007).