WSD for Assamese Language
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Abstract
Word sense ambiguity comes about the use of lexemes associated with more than one sense. In this research work, an improvement has been proposed and evaluated for our previously developed Assamese Word-Sense Disambiguation (WSD) system where potential outcomes of using semantic features were evaluated up to a limited extent. As semantic relationship information has a good effect in most of the natural language processing (NLP) tasks, in this work, the system is developed based on supervised learning approach using Naïve Bayes classifier with syntactic as well as semantic features. The performance measure of the overall system has been improved up to 91.11% in terms of F1-measure as compared to 86% of the previously developed system by incorporating the Semantically Related Words (SRW) feature in our feature set.
Keywords
Word sense ambiguity Naïve Bayes classifier Semantic feature Corpus Prior probabilityReferences
- 1.Jurafsky, D.: Speech & Language Processing. Pearson Education, India (2000)Google Scholar
- 2.Kaplan, A.: An experimental study of ambiguity and context. Mech. Transl. 2(2), 39–46 (1955)Google Scholar
- 3.Weaver, W.: Translation. Mach. Transl. Lang. 14, 15–23 (1955)Google Scholar
- 4.Borah, P.P., Talukdar, G., Baruah, A.: Assamese word sense disambiguation using supervised learning. In: 2014 International Conference on Contemporary Computing and Informatics (IC3I). IEEE (2014)Google Scholar
- 5.Sarmah, J., Sarma, S.K.: Word sense disambiguation for Assamese. In: 2016 IEEE 6th International Conference on Advanced Computing (IACC). IEEE (2016)Google Scholar
- 6.Sarmah, J., Sarma, S.K.: Decision tree based supervised word sense disambiguation for Assamese. Int. J. Comput. Appl. 141(1) (2016)Google Scholar
- 7.Sharma, P., Sharma, U., Kalita, J.: Suffix stripping based NER in Assamese for location names. In: 2012 2nd National Conference on Computational Intelligence and Signal Processing (CISP). IEEE (2012)Google Scholar
- 8.Le, C.A., Shimazu, A.: High WSD accuracy using Naïve Bayesian classifier with rich features. In: Proceedings of the 18th Pacific Asia Conference on Language, Information and Computation (2004)Google Scholar
- 9.Gale, W.A., Church, K.W., Yarowsky, D.: A method for disambiguating word senses in a large corpus. Comput. Humanit. 26(5-6), 415–439 (1992)CrossRefGoogle Scholar
- 10.Smadja, F.A.: Lexical co-occurrence: The missing link. Literary Linguist. Comput. 4(3), 163–168 (1989)CrossRefGoogle Scholar
- 11.Yarowsky, D.: One sense per collocation. Pennsylvania University Philadelphia, Department of Computer and Information Science (1993)Google Scholar
- 12.Pedersen, T., Patwardhan, S., Michelizzi, J.: WordNet:: similarity: measuring the relatedness of concepts. Demonstration papers at HLT-NAACL 2004. Association for Computational Linguistics (2004)Google Scholar