Global Word Sense Disambiguation of Polysemous Words in Telugu Language
Suneetha Eluri, Vasu Kumar Pilli2
1Dr. Suneetha Eluri*, Assistant Professor, Department of CSE, JNTUK – UCEK, Kakinada, India.
2Vasu Kumar Pilli, MTech (IT), Department of CSE, JNTUK – UCEK, Kakinada, India.
Manuscript received on October 05, 2020. | Revised Manuscript received on October 25, 2020. | Manuscript published on October 30, 2020. | PP: 420-425 | Volume-10 Issue-1, October 2020. | Retrieval Number: 100.1/ijeat.A19151010120 | DOI: 10.35940/ijeat.A1915.1010120
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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: Word Sense Disambiguation (WSD) is a significant issue in Natural Language Processing (NLP). WSD refers to the capacity of recognizing the correct sense of a word in a given context. It can improve numerous NLP applications such as machine translation, text summarization, information retrieval, or sentiment analysis. This paper proposes an approach named ShotgunWSD. Shotgun WSD is an unsupervised and knowledgebased algorithm for global word sense disambiguation. The algorithm is motivated by the Shotgun sequencing technique. Shotgun WSD is proposed to disambiguate the word senses of Telugu document with three functional phases. The Shotgun WSD achieves the better performance than other approaches of WSD in the disambiguating sense of ambiguous words in Telugu documents. The dataset is used in the Indo-WordNet.
Keywords: Shotgun sequencing, Word sense disambiguation, Word embedding, Telugu.