PI: Nisansa de Silva
The Knowledge Representation project investigates methods for structuring, aligning, and reasoning over knowledge extracted from language, with particular emphasis on low-resource settings, domain-specific semantics, and intelligent information access.
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.
PI: Nisansa de Silva
We propose to build and analyze Sinhala language resources, datasets, and models to strengthen NLP research for this low-resource language, while connecting it to English and Tamil through bilingual lexicons, embeddings, and cross-lingual methods.
Theses: MSc Major Component Research
Gathika Ratnayaka, "Minimizing domain bias when adapting sentiment analysis techniques to the legal domain", University of Moratuwa, 2022
Theses: MSc Minor Component Research
Sadeep Gunathilaka, "Automated User Review Analysis To Facilitate Potential Mobile Application Evolution", University of Moratuwa, 2025
Kasun Wickramasinghe, "Bilingual Lexicon Induction for the Sinhala-English Language Pair", University of Moratuwa, 2024
Journal Papers
Gathika Ratnayaka, Nisansa de Silva, Amal Shehan Perera, Gayan Kavirathne, Thirasara Ariyarathna, and Anjana Wijesinghe, "Context Sensitive Verb Similarity Dataset for Legal Information Extraction", Data, vol. 7, no. 7, 2022. doi: 10.3390/data7070087
Vindula Jayawardana, Dimuthu Lakmal, Nisansa de Silva, Amal Shehan Perera, Keet Sugathadasa, Buddhi Ayesha, and Madhavi Perera, "Word Vector Embeddings and Domain Specific Semantic based Semi-Supervised Ontology Instance Population", International Journal on Advances in ICT for Emerging Regions, vol. 10, no. 1, pp. 1, 2017. doi: 10.4038/icter.v11i1.7191
Conference Papers
Kasun Wickramasinghe and Nisansa de Silva, "Sinhala-English Word Embedding Alignment: Introducing Datasets and Benchmark for a Low Resource Language", in Proceedings of the 37th Pacific Asia Conference on Language, Information and Computation, 2023, pp. 424--435.
Kasun Wickramasinghe and Nisansa de Silva, "Sinhala-English Parallel Word Dictionary Dataset", in 2023 IEEE 17th International Conference on Industrial and Information Systems (ICIIS), 2023, pp. 61--66. doi: 10.1109/ICIIS58898.2023.10253560
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
