Measuring semantic similarity between words using web search engines. D Bollegala, Y Matsuo, M Ishizuka www 7 (2007), 757-766, 2007 | 826 | 2007 |
Cross-domain sentiment classification using a sentiment sensitive thesaurus D Bollegala, D Weir, J Carroll IEEE transactions on knowledge and data engineering 25 (8), 1719-1731, 2012 | 336 | 2012 |
A web search engine-based approach to measure semantic similarity between words D Bollegala, Y Matsuo, M Ishizuka IEEE Transactions on knowledge and Data Engineering 23 (7), 977-990, 2010 | 261 | 2010 |
Using multiple sources to construct a sentiment sensitive thesaurus for cross-domain sentiment classification D Bollegala, D Weir, JA Carroll Proceedings of the 49th annual meeting of the Association for Computational …, 2011 | 187 | 2011 |
Social media and pharmacovigilance: a review of the opportunities and challenges R Sloane, O Osanlou, D Lewis, D Bollegala, S Maskell, M Pirmohamed British journal of clinical pharmacology 80 (4), 910-920, 2015 | 165 | 2015 |
Relational duality: Unsupervised extraction of semantic relations between entities on the web DT Bollegala, Y Matsuo, M Ishizuka Proceedings of the 19th international conference on World wide web, 151-160, 2010 | 157 | 2010 |
Gender-preserving debiasing for pre-trained word embeddings M Kaneko, D Bollegala arXiv preprint arXiv:1906.00742, 2019 | 153 | 2019 |
Explanation in AI and law: Past, present and future K Atkinson, T Bench-Capon, D Bollegala Artificial Intelligence 289, 103387, 2020 | 151 | 2020 |
Cross-domain sentiment classification using sentiment sensitive embeddings D Bollegala, T Mu, JY Goulermas IEEE Transactions on Knowledge and Data Engineering 28 (2), 398-410, 2015 | 151 | 2015 |
A bottom-up approach to sentence ordering for multi-document summarization D Bollegala, N Okazaki, M Ishizuka Information processing & management 46 (1), 89-109, 2010 | 147 | 2010 |
Frustratingly Easy Meta-Embedding--Computing Meta-Embeddings by Averaging Source Word Embeddings J Coates, D Bollegala arXiv preprint arXiv:1804.05262, 2018 | 123 | 2018 |
Debiasing pre-trained contextualised embeddings M Kaneko, D Bollegala arXiv preprint arXiv:2101.09523, 2021 | 121 | 2021 |
Measuring the similarity between implicit semantic relations from the web DT Bollegala, Y Matsuo, M Ishizuka Proceedings of the 18th international conference on World wide web, 651-660, 2009 | 109 | 2009 |
“touching to see” and “seeing to feel”: Robotic cross-modal sensory data generation for visual-tactile perception JT Lee, D Bollegala, S Luo 2019 International Conference on Robotics and Automation (ICRA), 4276-4282, 2019 | 89 | 2019 |
Spinning multiple social networks for semantic web Y Matsuo, M Hamasaki, Y Nakamura, T Nishimura, K Hasida, H Takeda, ... Proceedings of the National Conference on Artificial Intelligence 21 (2), 1381, 2006 | 89 | 2006 |
Joint word representation learning using a corpus and a semantic lexicon D Bollegala, M Alsuhaibani, T Maehara, K Kawarabayashi Proceedings of the AAAI Conference on Artificial Intelligence 30 (1), 2016 | 78 | 2016 |
Unsupervised cross-domain word representation learning D Bollegala, T Maehara, K Kawarabayashi arXiv preprint arXiv:1505.07184, 2015 | 78 | 2015 |
Automatic discovery of personal name aliases from the web D Bollegala, Y Matsuo, M Ishizuka IEEE Transactions on Knowledge and Data Engineering 23 (6), 831-844, 2010 | 77 | 2010 |
DeepGraphMolGen, a multi-objective, computational strategy for generating molecules with desirable properties: a graph convolution and reinforcement learning approach Y Khemchandani, S O’Hagan, S Samanta, N Swainston, TJ Roberts, ... Journal of cheminformatics 12, 1-17, 2020 | 75 | 2020 |
Learning word meta-embeddings by autoencoding D Bollegala, C Bao Proceedings of the 27th international conference on computational …, 2018 | 70 | 2018 |