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
We propose to advance social media text analysis by combining linguistic study, preprocessing, and deep learning models to better capture sentiment, structure, and meaning in informal, large-scale user-generated text.
Conference Papers
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
N. H. N. D. de Silva, C. S. N. J. Fernando, M. K. D. T. Maldeniya, D. N. C. Wijeratne, A. S. Perera, and B Goertzel, "SeMap-Mapping Dependency Relationships into Semantic Frame Relationships", in Engineering Research Unit Research Seminar, December. 2011.
Preprints
Nisansa de Silva, Danaja Maldeniya, and Chamilka Wijeratne, "Subject Specific Stream Classification Preprocessing Algorithm for Twitter Data Stream", arXiv preprint arXiv:1705.09995, 2017. doi: 10.48550/ARXIV.1705.09995
