Gujarati Language: Research Issues, Resources and Proposed Method on Word Sense Disambiguation
Tarjni Vyas1, Amit Ganatra2
1Tarjni Vyas, Department of Computer Science and Engineering, Institute of Technology, Nirma University, Ahmedabad (Gujarat), India.
2Amit Ganatra, Dean, Department of Technology and Engineering, Devang Patel Institute of Advance Technology & Research DEPSTAR, Charotar University of Science and Technology University, Anand (Gujarat), India.
Manuscript received on 20 October 2019 | Revised Manuscript received on 25 October 2019 | Manuscript Published on 02 November 2019 | PP: 3745-3749 | Volume-8 Issue-2S11 September 2019 | Retrieval Number: B14830982S1119/2019©BEIESP | DOI: 10.35940/ijrte.B1483.0982S1119
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© The Authors. 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: Gujarati Word Sense Disambiguation (WSD) is an exceptionally complex when it comes to Natural language handling because it needs to manage complexities found in a language. In this paper, the discussion has put forward about Guajarati language, Gujarati Wordnet and Gujarati word sense disambiguation. Accordingly, the deep learning approach is found to perform better in Gujarati WSD yet one of its weakness is the prerequisite of enormous information sources without which preparing is close to impossible. On the other hand, utilizes information sources to choose the meanings of words in a specific setting. Provided with that, deep learning approaches appear to be more suitable to manage word sense disambiguation; however, the process will always be challenging given the ambiguity of natural languages.
Keywords: Word Sense Disambiguation, Gujarati Language, Deep Learning, Natural language Processing, Lesk Algorithm, Wordnet.
Scope of the Article: Natural Language Processing