Or gate Bayesian networks for text classification: A discriminative alternative approach to multinomial naive Bayes

We propose a simple Bayesian network-based text classifier, which may be considered as a discriminative counterpart of the generative multinomial naive Bayes classifier. The method relies on the use of a fixed network topology with the arcs going form term nodes to class nodes, and also on a network parametrization based on noisy or gates. Comparative experiments of the proposed method with naive Bayes and Rocchio algorithms are carried out using three standard document collections.