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Development of an Approach for Disambiguating Ambiguous Hindi postposition

by Avneet Kaur
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 5 - Number 9
Year of Publication: 2010
Authors: Avneet Kaur
10.5120/939-1317

Avneet Kaur . Development of an Approach for Disambiguating Ambiguous Hindi postposition. International Journal of Computer Applications. 5, 9 ( August 2010), 25-32. DOI=10.5120/939-1317

@article{ 10.5120/939-1317,
author = { Avneet Kaur },
title = { Development of an Approach for Disambiguating Ambiguous Hindi postposition },
journal = { International Journal of Computer Applications },
issue_date = { August 2010 },
volume = { 5 },
number = { 9 },
month = { August },
year = { 2010 },
issn = { 0975-8887 },
pages = { 25-32 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume5/number9/939-1317/ },
doi = { 10.5120/939-1317 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:53:50.076250+05:30
%A Avneet Kaur
%T Development of an Approach for Disambiguating Ambiguous Hindi postposition
%J International Journal of Computer Applications
%@ 0975-8887
%V 5
%N 9
%P 25-32
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this survey paper, we have taken the problem as “Development of an approach for disambiguating ambiguous Hindi postposition”. Word Sense Disambiguation (WSD) refers to the resolution of lexical semantic ambiguity and its goal is to attribute the correct senses to words in a given context. WSD is a most challenging problem in the area of NLP. We have chosen to develop an efficient algorithm for disambiguating ambiguous postpositions present in the Hindi language. We are taking this problem with the case study of existing Hindi-Punjabi Machine Translation System. Thus the disambiguation will be done from the machine translation point of view. This is mainly used for removing the ambiguity from the corpus.

References
  1. Yarowsky, D.1995. “Unsupervised Word Sense Disambiguation Rivaling Supervised Methods,” Proceedings of the 33rd annual meeting on Association for Computational Linguistics.
  2. Dekang Lin, 1997. "Using Syntactic Dependency as Local Context to resolve word sense Ambiguity.
  3. Rigau, G., 1997. Combining unsupervised lexical knowledge methods for word sense disambiguation. Proceedings of the 35th annual meeting on Association for Computational Linguistics.
  4. Ide and Veronis (1998) “Performance Metrics for Word Sense Disambiguation”.
  5. Hwee Tou Ng, Bin Wang, and Yee Seng Chan, 2002. “Parallel Texts for Word Sense Disambiguation”. In Proceeding of the 2002 Conference on Empirical Methods in Natural Language Processing.
  6. Peter D.Turney. 2003. Coherent key phrase extraction via Web Mining. In Proceeding of the Eighteenth International Joint Conference on Artificial Intelligence (IJCAI-03).
  7. Anagha Kulkarni, Michael Heilman, Maxine Eskenaz and Jamie Callan, 2006. “Word Sense Disambiguation for Vocabulary Learning”. Proceedings of the Ninth Proceeding of the 2002 Conference on Empirical Methods.
  8. Manish Sinha, Mahesh Kumar Reddy , Prabhakar Pande, Laxmi Kashyap & Pushpak Bhattacharyya, 2004. “Hindi Word Sense Disambiguatio”, International Symposium on machine translation, NLP and Translation support system.
  9. Timothy Baldwin, Su Nam Kim, Francis Bond, Sanae Fujita, David Martinez and Takaaki Tanaka, 1986. “MRD-based Word Sense Disambiguation”.
Index Terms

Computer Science
Information Sciences

Keywords

Word sense disambiguation (WSD) Natural Language Processing (NLP) Postpositions Machine Translation (MT).

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