CFP last date
20 January 2025
Reseach Article

Techniques for Disambiguation of Polysemy Words: A Review

by Vandita Singh, Krishan Kr. Saraswat
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 178 - Number 23
Year of Publication: 2019
Authors: Vandita Singh, Krishan Kr. Saraswat
10.5120/ijca2019919006

Vandita Singh, Krishan Kr. Saraswat . Techniques for Disambiguation of Polysemy Words: A Review. International Journal of Computer Applications. 178, 23 ( Jun 2019), 6-10. DOI=10.5120/ijca2019919006

@article{ 10.5120/ijca2019919006,
author = { Vandita Singh, Krishan Kr. Saraswat },
title = { Techniques for Disambiguation of Polysemy Words: A Review },
journal = { International Journal of Computer Applications },
issue_date = { Jun 2019 },
volume = { 178 },
number = { 23 },
month = { Jun },
year = { 2019 },
issn = { 0975-8887 },
pages = { 6-10 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume178/number23/30672-2019919006/ },
doi = { 10.5120/ijca2019919006 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:51:11.716819+05:30
%A Vandita Singh
%A Krishan Kr. Saraswat
%T Techniques for Disambiguation of Polysemy Words: A Review
%J International Journal of Computer Applications
%@ 0975-8887
%V 178
%N 23
%P 6-10
%D 2019
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The domain of Computational Linguistics involves the key task of Word Sense Disambiguation which aims to assign a meaning to particular word in terms of the context with which it is used in a sentence. The task of assigning the semantically correct meaning to a polysemy word in almost all the languages of the world stands out to be an open problem of research with considerably low accuracies achieved. The paper presents a meticulous review of the various techniques opted for disambiguation of polysemy words in various languages -English, Hindi, Nepalese, Tamil, Kannada, Telugu, Malayalam, Sinhala and German. Also, an insight into how the various approaches -supervised (involving corpora) and Unsupervised (clustering, meta thesaurus) to solving the above problems evolved over the years to get the accuracy improved. The applications include word processing, spell checking, content analysis, translation, improved search engines.

References
  1. M. Lesk, “Automatic sense disambiguation using machine readable dictionaries: how to tell a pine cone from an ice cream cone,” in Proc.5th annual international conference on Systems documentation, New York, USA, 1986, pp. 24 – 26. J. Clerk Maxwell, A Treatise on Electricity and Magnetism, 3rd ed., vol. 2. Oxford: Clarendon, 1892, pp.68–73.
  2. S. Banerjee and T. Pedersen, "An adapted lesk algorithm for word sense disambiguation using wordnet," in Third Interna tional Conference on Intelligent Text Processing and Computational Linguistics, Gelbukh, 2002.
  3. Eneko Agirre and German Rigau, "Word Sense Disambiguation using conceptual density," Proceedings of the 16th conference on Computational linguistics - Volume 1, 1996
  4. Wei Jan Lee and Edwin Mit, “Word Sense Disambiguation By Using Domain Knowledge”, International Conference on Semantic Technology and Information Retrieval 28-29 June 2011, Putrajaya, Malaysia, 978-1-61284-353-7/11/$26.00 ©2011 IEEE
  5. Sayali Charhate, Anurag Dani and Rekha Sugandhi, “Adding Intelligence to Non-corpus based Word Sense Disambiguation”, 2012 12th International Conference on Hybrid Intelligent Systems (HIS) 978-1-4673-5116-4/12/$31.00 ⃝c 2012 IEEE
  6. P. Sachdeva , S.Verma and S.K.Singh, “ An Improved Approach to Word Sense Disambiguation”, 978-1-4799-1812-6/14/$31.00 ©2014
  7. M. Sinha, M. K. Reddy, P. Bhattacharyya, P. Pandey, and L. Kashyap, "Hindi word sense disambiguation," Master's thesis, Indian Institute of Technology Bombay,Mumbai, India, 2004
  8. S. Vishwakarma, and C. Vishwakarma, “A graph based approach to word sense disambiguation for Hindi language,” India, International Journal of Scientific Research Engineering & Technology, vol. 1, pp. 313-318, August 2012.
  9. R. Sharma, “Word Sense Disambiguation for Hindi Language,” Diss. Tharpar University, India, 2008.
  10. N. Shrestha, A. V. H. Patrick, and S. K. Bista, "Resources for nepali word sense disambiguation," in IEEE International conference on Natural Language Processing and Knowledge Engineering (IEEE NLP-KE'08), Beijing, China, 2008.
  11. U. R. Dhungana and S. Shakya, "Word sense disambiguation in nepali language," in The Fourth International Conference on Digital Information and Communication Technology and Its Application (DICTAP2014), Bangkok, Thailand, 20l4, pp. 46-50.
  12. Udaya Raj Dhungana1, Subarna Shakya, Kabita Bara and Bharat Sharma , in IEEE 9th International Conference on Semantic Computing (IEEE ICSC 2015) 2015, Anaheim, California, USA 978- 1-4799-7935-6/15
  13. Bhaskaran S and Vaidehi , “Collocation Based Word Sense Disambiguation using clustering for Tamil”, V, K U Research Center,2003.
  14. Ch Mandakini and Dr K V N Sunitha, “Disambiguating the sense of verb in Telugu sentence using the argument structure”, International Journal of Computational Linguistics and Natural Language Processing Vol 1 Issue 5 December 2012
  15. S Parameswarappa and V N Narayana,, “Kannada Word Sense Disambiguation for Machine Translation,” International Journal of Computer Applications V olume 34– No.10, November 2011.
  16. R P Haroon “Malayalm Word Sense Disambiguation” Computational intelligence and computing research (ICCIC), IEEE,2010, E- ISBN:978- 1-4244-5967-4.
  17. Sreelakshmi Gopal and Rosna P Haroon, “ Malayalam Word Sense Disambiguation using Naïve Bayes Classifier”, International Conference on Advances in Human Machine Interaction (HMI - 2016), March 03-05, 2016, R. L. Jalappa Institute of Technology, Doddaballapur, Bangalore, India , 978-1-4673-8810-8/16/$31.00 ©2016 IEEE
  18. C. Marasinghe, S. Herath, and A. Herath, “Word sense disambiguation of Sinhala language with unsupervised learning,”in Proc. International Conference on Information Technology and Applications, Bathurst, Australia, November 2002, pp. 25-29
  19. J. Arukgoda ,V. Bandara,S.Bashani,V.Gamage and D.Wimalasuriya, “A Word Sense Disambiguation Technique for Sinhala” , in 4th International Conference on Artificial Intelligence with Applications in Engineering and Technology , 978-1-4799-7910-3/14 $31.00 © 2014 IEEE DOI 10.1109/ICAIET.2014.42
  20. V. Henrich, and E. Hinrichs “A comparative evaluation of word sense disambiguation algorithms for German,” in Proc. LREC’12,Istanbul, Turkey, 2012, pp. 576-583.
  21. S. Broscheit, A. Frank, D. Jehle, S. Ponzetto, D. Rehl, A. Summa, K.Suttner, and S. Vola, “Rapid bootstrapping of word sense disambiguation re-sources for German,”inProc.10th Konferenz zur Verarbeitung Natürlicher Sprache, Germany, 2010 pp. 19–27.
Index Terms

Computer Science
Information Sciences

Keywords

Natural Language Processing Word Sense Disambiguation WordNet Polysemy Words