Research on Machine Learning Techniques for POS Tagging in NLP
Aparna Bulusu1, Sucharita V2
1Aparna Bulusu, Research Scholar, Department of CSE, K L University Vaddeswaram, Vijaywada (Andhra Pradesh), India.
2Dr. Sucharita V, Professor, Department of CSE, Narayana Engineering College, Guntur, Nellore (Andhra Pradesh), India.
Manuscript received on 06 June 2019 | Revised Manuscript received on 30 June 2019 | Manuscript Published on 04 July 2019 | PP: 897-900 | Volume-8 Issue-1S4 June 2019 | Retrieval Number: A11650681S419/2019©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Natural Language Processing is an emerging area with applications like speech recognition, sentiment analysis, question answering systems, chat bots and the like. Current research is making heavy use of machine learning techniques for NLP Tasks Machine Learning is a subset of Artificial Intelligence with techniques based heavily on statistical and mathematical concepts. This paper attempts to list out the major categories of tasks under Natural Language Processing, and understand the commonly used machine learning techniques for the said tasks. Empirical tests have been performed to validate the findings of the literature survey and results are discussed.
Keywords: Natural Language Processing, Machine Learning, Brown Corpus, Classifiers, NLTK.
Scope of the Article: Machine Learning