PI: Nisansa de Silva
We propose to advance natural language processing for low-resource settings by leveraging data augmentation, transfer learning, and model adaptation techniques to overcome the scarcity of annotated data and linguistic resources.
PI: Nisansa de Silva
This project delves into the synergy between Natural Language Processing (NLP) and the legal domain, presenting novel solutions to enduring challenges.
Conference Papers
Keet Sugathadasa, Buddhi Ayesha, Nisansa de Silva, Amal Shehan Perera, Vindula Jayawardana, Dimuthu Lakmal, and Madhavi Perera, "Synergistic Union of Word2Vec and Lexicon for Domain Specific Semantic Similarity", in 2017 IEEE International Conference on Industrial and Information Systems (ICIIS), 2017, pp. 1--6. doi: 10.1109/ICIINFS.2017.8300343
Vindula Jayawardana, Dimuthu Lakmal, Nisansa de Silva, Amal Shehan Perera, Keet Sugathadasa, Buddhi Ayesha, and Madhavi Perera, "Semi-Supervised Instance Population of an Ontology using Word Vector Embedding", in 2017 Seventeenth International Conference on Advances in ICT for Emerging Regions (ICTer), 2017, pp. 1--7. doi: 10.1109/icter.2017.8257822 
Vindula Jayawardana, Dimuthu Lakmal, Nisansa de Silva, Amal Shehan Perera, Keet Sugathadasa, and Buddhi Ayesha, "Deriving a Representative Vector for Ontology Classes with Instance Word Vector Embeddings", in 2017 Seventh International Conference on Innovative Computing Technology (INTECH), 2017, pp. 79--84. doi: 10.1109/intech.2017.8102426
U. L. D. N. Gunasinghe, W. A. M. De Silva, N. H. N. D. de Silva, A. S. Perera, W. A. D. Sashika, and W. D. T. P. Premasiri, "Sentence Similarity Measuring by Vector Space Model", in Advances in ICT for Emerging Regions (ICTer), 2014 International Conference on, December. 2014, pp. 185--189. doi: 10.1109/ICTER.2014.7083899
