In related works that use the PMI (Morin et al., 2007), these probabilities are simply estimated using relative frequencies, as where f (x), f (y) is the document frequency of word x and word y, and f (x, y) is the cooccurrence frequency; n is the number of documents.
we assume that where the parameters for the two beta distributions are set to Prior information related to p(x) and the conditional probability p(x|y) can be incorporated by setting the hyper-parameters of the betadistribtutions.