Dimensional sentiment analysis using a regional CNN-LSTM model J Wang, LC Yu, KR Lai, X Zhang Proceedings of the 54th annual meeting of the association for computational …, 2016 | 660 | 2016 |
Refining word embeddings for sentiment analysis LC Yu, J Wang, KR Lai, X Zhang Proceedings of the 2017 conference on empirical methods in natural language …, 2017 | 257 | 2017 |
Building Chinese affective resources in valence-arousal dimensions LC Yu, LH Lee, S Hao, J Wang, Y He, J Hu, KR Lai, X Zhang Proceedings of the 2016 Conference of the North American Chapter of the …, 2016 | 176 | 2016 |
Refining word embeddings using intensity scores for sentiment analysis LC Yu, J Wang, KR Lai, X Zhang IEEE/ACM Transactions on Audio, Speech, and Language Processing 26 (3), 671-681, 2017 | 171 | 2017 |
Using a stacked residual LSTM model for sentiment intensity prediction J Wang, B Peng, X Zhang Neurocomputing 322, 93-101, 2018 | 143 | 2018 |
Tree-structured regional CNN-LSTM model for dimensional sentiment analysis J Wang, LC Yu, KR Lai, X Zhang IEEE/ACM Transactions on Audio, Speech, and Language Processing 28, 581-591, 2019 | 119 | 2019 |
Deep fusion feature learning network for MI-EEG classification J Yang, S Yao, J Wang Ieee Access 6, 79050-79059, 2018 | 90 | 2018 |
Predicting valence-arousal ratings of words using a weighted graph method LC Yu, J Wang, KR Lai, X Zhang Proceedings of the 53rd Annual Meeting of the Association for Computational …, 2015 | 62 | 2015 |
Community-based weighted graph model for valence-arousal prediction of affective words J Wang, LC Yu, KR Lai, X Zhang IEEE/ACM Transactions on Audio, Speech, and Language Processing 24 (11 …, 2016 | 59 | 2016 |
Conciseness is better: Recurrent attention LSTM model for document-level sentiment analysis Y Zhang, J Wang, X Zhang Neurocomputing 462, 101-112, 2021 | 42 | 2021 |
Ynu-hpcc at semeval-2018 task 1: Bilstm with attention based sentiment analysis for affect in tweets Y Zhang, J Wang, X Zhang Proceedings of The 12th International Workshop on Semantic Evaluation, 273-278, 2018 | 42 | 2018 |
Investigating dynamic routing in tree-structured LSTM for sentiment analysis J Wang, LC Yu, KR Lai, X Zhang Proceedings of the 2019 Conference on Empirical Methods in Natural Language …, 2019 | 38 | 2019 |
YNU-HPCC at EmoInt-2017: Using a CNN-LSTM model for sentiment intensity prediction Y Zhang, H Yuan, J Wang, X Zhang Proceedings of the 8th workshop on computational approaches to subjectivity …, 2017 | 35 | 2017 |
Contextual sentiment embeddings via bi-directional GRU language model J Wang, Y Zhang, LC Yu, X Zhang Knowledge-Based Systems 235, 107663, 2022 | 28 | 2022 |
Adversarial learning of sentiment word representations for sentiment analysis B Peng, J Wang, X Zhang Information Sciences 541, 426-441, 2020 | 28 | 2020 |
An attentive neural sequence labeling model for adverse drug reactions mentions extraction P Ding, X Zhou, X Zhang, J Wang, Z Lei Ieee Access 6, 73305-73315, 2018 | 27 | 2018 |
YNU-HPCC at SemEval 2017 task 4: Using a multi-channel CNN-LSTM model for sentiment classification H Zhang, J Wang, J Zhang, X Zhang Proceedings of the 11th International Workshop on Semantic Evaluation …, 2017 | 27 | 2017 |
Locally weighted linear regression for cross-lingual valence-arousal prediction of affective words J Wang, LC Yu, KR Lai, X Zhang Neurocomputing 194, 271-278, 2016 | 23 | 2016 |
A multi-dimensional relation model for dimensional sentiment analysis H Xie, W Lin, S Lin, J Wang, LC Yu Information Sciences 579, 832-844, 2021 | 22 | 2021 |
Hierarchical BERT with an adaptive fine-tuning strategy for document classification J Kong, J Wang, X Zhang Knowledge-Based Systems 238, 107872, 2022 | 21 | 2022 |