Publication Type : Conference Paper
Thematic Areas : Scientific reports
Publisher : Association for Computational Linguistics, IIT Kharagpur,
Source : Proceedings of the 6th International Sanskrit Computational Linguistics Symposium, Association for Computational Linguistics, IIT Kharagpur, India (2019)
Url : https://www.aclweb.org/anthology/W19-7504
Campus : Coimbatore
School : School of Engineering
Center : Computational Engineering and Networking
Department : Computer Science, Electronics and Communication
Year : 2019
Abstract : In this paper, we propose a classification framework for finding the compound words from a given Sanskrit text. The compound word identification plays a significant role in learning the elucidations of verses in Ayurveda text books which are written in Sanskrit. This process was modelled using several classification algorithms and we examined their efficacy with varying word embedding dimensions. Sanskrit words were vectorized using fastText word embedding method. The results show that the performance of K-Nearest Neighbor is better than other classifiers and the prediction accuracy is 90.38%.
Cite this Research Publication : B. Premjith, Chandni Chandran V., Shriganesh Bhat, Dr. Soman K. P., and Prabaharan P., “A Machine Learning Approach for Identifying Compound Words from a Sanskrit Text”, in Proceedings of the 6th International Sanskrit Computational Linguistics Symposium, IIT Kharagpur, India, 2019.