Another useful form of knowledge for topic discoveries is based on word semantics Chemudugunta et al., 2008;Hu et al., 2014;Jagarlamudi et al., 2012;Doshi-Velez et al., 2015).
word embedding (Pennington et al., 2014;Goldberg and Levy, 2014), in which bag of words are transformed into vector representations so that contexts are embedded into those word vectors, are used as semantic regularities to enhance topic models (Nguyen et al., 2015;Li et al., 2016;Das et al., 2015;Batmanghelich et al., 2016).