Bayesian Nets in Syntactic Categorization of Novel Words

This paper presents an application of a Dynamic Bayesian Network (DBN) to the task of assigning Part-of-Speech (PoS) tags to novel text. This task is particularly challenging for non-standard corpora, such as Internet lingo, where a large proportion of words are unknown. Previous work reveals that PoS tags depend on a variety of morphological and contextual features. Representing these dependencies in a DBN results into an elegant and effective PoS tagger.