Natural Language Processing Based Part of Speech Tagger using Hidden Markov Model








Abstract

In various natural language processing applications, PART-OF-SPEECH (POS) tagging is performed as a preprocessing step. For making POS tagging accurate, various techniques have been explored. But in Indian languages, not much work has been done. This paper describes the methods to build a Part of speech tagger by using hidden markov model. Supervised learning approach is implemented in which, already tagged sentences in malayalam is used to build hidden markov model.


Modules


Algorithms


Software And Hardware

Textual Question Answering for Semantic Parsing in Natural Language Processing