Unsupervised Part of Speech Tagging for Persian
Tayebeh Mosavi Miangah · International Journal of Artificial Intelligence & Applications · 2012
In this paper we present a rather novel unsupervised method for part of speech (below POS) disambiguation which has been applied to Persian.This method known as Iterative Improved Feedback (IIF) Model, which is a heuristic one, uses only a raw corpus of Persian as well as all possible tags for every word in that corpus as input.During the process of tagging, the algorithm passes through several iterations corresponding to n-gram levels of analysis to disambiguate each word based on a previously defined threshold.The total accuracy of the program applying in Persian texts has been calculated as 93 percent, which seems very encouraging for POS tagging in this language.