| Supervised and traditional term weighting methods for automatic text categorization M Lan, CL Tan, J Su, Y Lu IEEE transactions on pattern analysis and machine intelligence 31 (4), 721-735, 2008 | 725 | 2008 |
| A comprehensive comparative study on term weighting schemes for text categorization with support vector machines M Lan, CL Tan, HB Low, SY Sung Special interest tracks and posters of the 14th international conference on …, 2005 | 211 | 2005 |
| Initialization of cluster refinement algorithms: A review and comparative study J He, M Lan, CL Tan, SY Sung, HB Low 2004 IEEE international joint conference on neural networks (IEEE Cat. No …, 2004 | 190 | 2004 |
| Proposing a new term weighting scheme for text categorization M Lan, CL Tan, HB Low AAAI 6, 763-768, 2006 | 165 | 2006 |
| Predicting discourse connectives for implicit discourse relation recognition ZM Zhou, Y Xu, ZY Niu, M Lan, J Su, CL Tan Coling 2010: Posters, 1507-1514, 2010 | 156 | 2010 |
| MRAEA: an efficient and robust entity alignment approach for cross-lingual knowledge graph X Mao, W Wang, H Xu, M Lan, Y Wu Proceedings of the 13th International Conference on Web Search and Data …, 2020 | 154 | 2020 |
| Ecnu: One stone two birds: Ensemble of heterogenous measures for semantic relatedness and textual entailment J Zhao, T Zhu, M Lan Proceedings of the 8th International Workshop on Semantic Evaluation …, 2014 | 135 | 2014 |
| A comparative study on term weighting schemes for text categorization M Lan, SY Sung, HB Low, CL Tan Proceedings. 2005 IEEE International Joint Conference on Neural Networks …, 2005 | 130 | 2005 |
| Relational reflection entity alignment X Mao, W Wang, H Xu, Y Wu, M Lan Proceedings of the 29th ACM International Conference on Information …, 2020 | 117 | 2020 |
| Multi-task attention-based neural networks for implicit discourse relationship representation and identification M Lan, J Wang, Y Wu, ZY Niu, H Wang Proceedings of the 2017 conference on empirical methods in natural language …, 2017 | 117 | 2017 |
| Joint type inference on entities and relations via graph convolutional networks C Sun, Y Gong, Y Wu, M Gong, D Jiang, M Lan, S Sun, N Duan Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019 | 109 | 2019 |
| Graph-based dependency parsing with graph neural networks T Ji, Y Wu, M Lan Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019 | 107 | 2019 |
| Boosting the speed of entity alignment 10×: Dual attention matching network with normalized hard sample mining X Mao, W Wang, Y Wu, M Lan Proceedings of the Web Conference 2021, 821-832, 2021 | 78 | 2021 |
| A refined end-to-end discourse parser J Wang, M Lan Proceedings of the Nineteenth Conference on Computational Natural Language …, 2015 | 76 | 2015 |
| Leveraging synthetic discourse data via multi-task learning for implicit discourse relation recognition M Lan, Y Xu, ZY Niu Proceedings of the 51st Annual Meeting of the Association for Computational …, 2013 | 75 | 2013 |
| Scaling up open tagging from tens to thousands: Comprehension empowered attribute value extraction from product title H Xu, W Wang, X Mao, X Jiang, M Lan Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019 | 74 | 2019 |
| Ecnu at SemEval-2017 task 1: Leverage kernel-based traditional nlp features and neural networks to build a universal model for multilingual and cross-lingual semantic textual … J Tian, Z Zhou, M Lan, Y Wu Proceedings of the 11th international workshop on semantic evaluation …, 2017 | 74 | 2017 |
| Exploiting user profile information for answer ranking in cqa ZM Zhou, M Lan, ZY Niu, Y Lu Proceedings of the 21st international conference on World Wide Web, 767-774, 2012 | 64 | 2012 |
| From alignment to assignment: Frustratingly simple unsupervised entity alignment X Mao, W Wang, Y Wu, M Lan arXiv preprint arXiv:2109.02363, 2021 | 50 | 2021 |
| A multi-task learning approach for improving product title compression with user search log data J Wang, J Tian, L Qiu, S Li, J Lang, L Si, M Lan Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 46 | 2018 |
Chew Lim TanProfessor of Computer Science, National University of SingaporeVerified email at comp.nus.edu.sg
