Automatic Generation of Synsets for Wordnet of Hindi Language

Priyank Pandey, Manju Khari, Raghavendra Kumar and Dac-Nhuong Le
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Priyank Pandey: Department of Computer Science, Graphic Era University, Dehradun, India
Manju Khari: Computer Science and Engineering Department, AIACTR, Delhi, India
Raghavendra Kumar: Computer Science and Engineering Department, LNCT College, Indore, India
Dac-Nhuong Le: Faculty of Information Technology, Haiphong University, Haiphong, Vietnam

International Journal of Natural Computing Research (IJNCR), 2018, vol. 7, issue 2, 31-47

Abstract: India is a land of 122 languages and numerous dialects. Lack of competent lexical resources for Indian languages is a ubiquitous fact, which negatively affects the development of tools for NLP of Indian languages. Recent advancements like the Indo WordNet project has significantly contributed to dealing with the scarcity of lexicons, but the progress and coverage is a matter of dispute. The bottlenecks, cost, time, and skilled lexicographers further slackens the progress. In this article, the authors propose a technique to automate the generation of lexical entries using a machine learning approach which visibly expedites the process of lexicon generation like WordNet. The reluctance to adopt an automated approach is majorly credited to a lack of accuracy, the inability to capture a regional touch of a language, incorrect back-translation, etc. To overcome this issue, the author will use Wikipedia to validate the synsets.

Date: 2018
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