Arabic/english word translation disambiguation approach based on naive bayesian classifier

We present a word sense disambiguation approach with application in machine translation from Arabic to English. The approach consists of two main steps: First, a natural language processing method that deals with the rich morphology of Arabic language and second, the translation including word sense disambiguation. The main innovative features of this approach are the adaptation of the Naive Bayesian approach with new features to consider the Arabic language properties and the exploitation of a large parallel corpus to find the correct sense based on its cohesion with words in the training corpus. We expect that the resulting system will overcome the problem of the absence of the vowel signs, which is the main reason for the translation ambiguity between Arabic and other languages.