Word Sense Disambiguation: An Empirical Survey
J. Sreedhar1, S. Viswanadha Raju2, A. Vinaya Babu3, Amjan Shaik4, P. Pavan Kumar5

1J. Sreedhar, Sr. Associate Professor in Computer Science & Engineering, ECET, Hyderabad, India.
2Dr. S. Viswanadha Raju, Professor in CSE, SIT, JNT University, Hyderabad, India.
3Dr. A. Vinaya Babu, Professor in CSE & Principal in JNTUniversity, Hyderabad, India.
4Amjan Shaik, Student in CSE & Principal in JNTUniversity, Hyderabad, India.
5P. Pavan Kumar,  Student in CSE & Principal in JNTUniversity, Hyderabad, India.

Manuscript received on April 11, 2012. | Revised Manuscript received on April 14, 2012. | Manuscript published on May 05, 2012. | PP: 494-503 | Volume-2 Issue-2, May 2012 . | Retrieval Number: B0591042212/2012©BEIESP
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© The Authors. Published By: 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: Word Sense Disambiguation(WSD) is a vital area which is very useful in today’s world. Many WSD algorithms are available in literature, we have chosen to opt for an optimal and portable WSD algorithms. We are discussed the supervised, unsupervised, and knowledge-based approaches for WSD. This paper will also furnish an idea of few of the WSD algorithms and their performances, Which compares and asses the need of the word sense disambiguity.

Keywords: Supervised, Unsupervised, Knowledge-based , WSD.