Research Cell: An International Journal of Engineering Sciences

Open Access Open Access  Restricted Access Subscription Access

Polysemy Identification for Dogri Language


Affiliations
1 Department of Computer Science and IT, University of Jammu, Jammu, India
 

Many of the NLP systems fails to identify the Word Sense Disambiguation and because of the Polysemy. This problem persists in almost all the NLP systems for the Indian languages. The approach for the identification of this problem depend on language specific knowledge based on the context of the polysemy words and some pre-existing natural language processing (NLP) tools for the low resourced languages like Dogri. In this paper a model is proposed for the polysemy identifications and management based on the context. The proposed model will suggest the meaning based on the context.

Keywords

Polysemy, Dogri, Word Sense Disambiguation.
User
Notifications
Font Size

  • R. Rao and J. S. Kallimani, "Analysis of polysemy words in Kannada sentences based on parts of speech," 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2016, pp. 500-504, doi: 10.1109/ICACCI.2016.7732095.

  • Y. Lin, M. Yu and C. Lin, "A combined approach to the polysemy problems in a Chinese to Taiwanese TTS system," 2010 7th International Symposium on Chinese Spoken Language Processing, 2010, pp. 455-459, doi: 10.1109/ISCSLP.2010.5684482.

  • H. Miao and Y. Zhang, "Construction of Polysemy table and search engine based on inverted index," 2012 9th International Conference on Fuzzy Systems and Knowledge Discovery, 2012, pp. 2287-2290, doi: 10.1109/FSKD.2012.6234156.

  • C. Prasad and J. S. Kallimani, "A novel approach to identify polysemy words in Indian regional language," 2016 International Conference on Electrical, Electronics, Communication, Computer and Optimization Techniques (ICEECCOT), 2016, pp. 179-182, doi: 10.1109/ICEECCOT.2016.7955210.

  • U. R. Dhungana, S. Shakya, K. Baral and B. Sharma, "Word Sense Disambiguation using WSD specific WordNet of polysemy words," Proceedings of the 2015 IEEE 9th International Conference on Semantic Computing (IEEE ICSC 2015), 2015, pp. 148-152, doi: 10.1109/ICOSC.2015.7050794.

  • Z. Qin, H. Lian, T. He and B. Luo, "Cluster Correction on Polysemy and Synonymy," 2017 14th Web Information Systems and Applications Conference (WISA), 2017, pp. 136138, doi: 10.1109/WISA.2017.45.

  • Y. Lin, M. Yu and C. Huang, "The Polysemy Problems, an Important Issue in a Chinese to Taiwanese TTS System," 2008 Congress on Image and Signal Processing, 2008, pp. 361365, doi: 10.1109/CISP.2008.728.

  • Maria Lapata. 2001. A corpus-based account of regular polysemy: the case of contextsensitive adjectives. In Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies (NAACL '01). Association for Computational Linguistics, USA, 1–8. DOI:https://doi.org/10.3115/1073336.1073345

  • Jamwal S.S., Gupta P., Sen V.S. (2021) Hybrid Model for Generation of Verbs of Dogri Language. In: Singh T.P., Tomar R., Choudhury T., Perumal T., Mahdi H.F. (eds) Data Driven Approach Towards Disruptive Technologies. Studies in Autonomic, Data-driven and Industrial Computing. Springer, Singapore. https://doi.org/10.1007/978-981-15-9873-9_39.

  • Gupta P., Jamwal S.S. (2021) Designing and Development of Stemmer of Dogri Using Unsupervised Learning. In: Marriwala N., Tripathi C.C., Jain S., Mathapathi S. (eds) Soft Computing for Intelligent Systems. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-16-1048-6_11.


Abstract Views: 377

PDF Views: 2




  • Polysemy Identification for Dogri Language

Abstract Views: 377  |  PDF Views: 2

Authors

Shubhnandan S. Jamwal
Department of Computer Science and IT, University of Jammu, Jammu, India

Abstract


Many of the NLP systems fails to identify the Word Sense Disambiguation and because of the Polysemy. This problem persists in almost all the NLP systems for the Indian languages. The approach for the identification of this problem depend on language specific knowledge based on the context of the polysemy words and some pre-existing natural language processing (NLP) tools for the low resourced languages like Dogri. In this paper a model is proposed for the polysemy identifications and management based on the context. The proposed model will suggest the meaning based on the context.

Keywords


Polysemy, Dogri, Word Sense Disambiguation.

References