Towards a Richer IndoWordNet with New Additions for Hindi and Gujarati Languages

The authors of this research paper present a mech-anism for dealing with loanwords, missing words, and newly de-veloped terms inclusion issues in WordNets. WordNet has evolved as one of the most prominent Natural Language Processing (NLP) toolkits. This mechanism can be used to improve the WordNet of any language. The authors chose to work with the Hindi and Gujarati languages in this research work to achieve a higher quality research aspect because these are the languages with major dialects. The research work used more than 5000 Hindi verse-based data corpus instead of a prose-based data corpus.As a result, nearly 14000 Hindi words were discovered that were not present in the popular Hindi IndoWordNet, accounting for 13.23 percent of the total existing word count of 105000+. Working with idioms was a distinct method for the Gujarati language. Around 3500 idioms data were used, and nearly 900 Gujarati terms were discovered that did not exist in the IndoWordNet, accounting for nearly 1.4 percent of the total of 64000+ Gujarati words in the IndoWordNet. It will also contribute almost 14000 Hindi words and around 900 Gujarati words to the IndoWordNet project.

@article{Audichya2022,
  title     = {Towards a Richer IndoWordNet with New Additions for Hindi and Gujarati Languages},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {13},
  number    = {7},
  year      = {2022},
  publisher = {The Science and Information Organization},
  author    = {Milind Kumar Audichya and Jatinderkumar R. Saini and Jatin C. Modh},
  doi       = {10.14569/IJACSA.2022.0130797},
  url       = {https://doi.org/10.14569/IJACSA.2022.0130797}
}