This paper describes an experimental comparison between two standard supervised learning methods, namely Naive Bayes and Exemplar--based classification, on the Word Sense Disambiguation (WSD) problem.
In this paper we propose the type of Bayesian networks that we call the hierarchical Bayesian network (HBN) classifiers. We present algorithms for the construction of the HBN classifiers and test them on the Reuters text categorization test collection
This list is intended to introduce some of the tools of Bayesian statistics and machine learning that can be useful to computational research in cognitive science.