Sharif Digital Repository

In this thesis the usage of probabilistic reasoning in collaborative filtering is investigated. The problem of predicting users' rating is formulated as a Bayesian decision problem and a generative probabilistic model is used in order to find the optimal decision. Two different probabilistic models are considered: user based model and rating based model. In user based model prediction of ratings is based on structural learning of Bayesian networks. In rating based model, we assume a predefined Bayesian network represents the joint distribution over model variables and rating prediction is carried out using McMc inference method. MovieLens dataset is chosen to evaluate and compare the results...