Graph-based word sense disambiguation in Telugu language

Article type: Research Article

Authors: Koppula, Neeraja^{a; *} | Rani, B. Padmaja^b | Srinivas Rao, Koppula^a

Affiliations: [a] Department CSE, MLR Institute of Technology, Hyderabad, India | [b] Department CSE, JNTUCEH, Hyderabad, India

Correspondence: [*] Corresponding author: Neeraja Koppula, Department CSE, MLR Institute of Technology, Hyderabad, India. %****␣kes-23-kes190399_temp.tex␣Line␣25␣**** E-mail: Kneeraja123\[email protected].

Abstract: In Natural Language Processing, word sense disambiguation (WSD) is an open challenge which improves the performance of the applications such as machine translation and information retrieval system. Many verbal languages will have many ambiguous words. The meaning of these ambiguous words differ per context. To choose the correct meaning of the word in the given context is known as WSD. In this article, the proposed work is to develop a WSD system using machine learning technique and knowledge-based approach for Telugu language. The knowledge resource used to develop the WSD system is Lexical Knowledge Base (LKB). The efficiency of WSD system is good when compared with other unsupervised approaches.

Keywords: Telugu language, word sense disambiguation, Natural Language Processing, knowledge-based approach

DOI: 10.3233/KES-190399

Journal: International Journal of Knowledge-based and Intelligent Engineering Systems, vol. 23, no. 1, pp. 55-60, 2019