Haiyun Peng
Cited by
Cited by
Targeted aspect-based sentiment analysis via embedding commonsense knowledge into an attentive LSTM
Y Ma, H Peng, E Cambria
Proceedings of AAAI, 5876-5883, 2018
Knowing what, how and why: A near complete solution for aspect-based sentiment analysis
H Peng, L Xu, L Bing, F Huang, W Lu, L Si
Proceedings of the AAAI conference on artificial intelligence 34 (05), 8600-8607, 2020
Sentic LSTM: a hybrid network for targeted aspect-based sentiment analysis
Y Ma, H Peng, T Khan, E Cambria, A Hussain
Cognitive Computation 10, 639-650, 2018
Sentiment and Sarcasm Classification with Multitask Learning
N Majumder, S Poria, H Peng, N Chhaya, E Cambria, A Gelbukh
IEEE Intelligent Systems 34 (3), 2019
Ensemble application of convolutional neural networks and multiple kernel learning for multimodal sentiment analysis
S Poria, H Peng, A Hussain, N Howard, E Cambria
Neurocomputing 261, 217-230, 2017
A review of sentiment analysis research in Chinese language
H Peng, E Cambria, A Hussain
Cognitive Computation 9, 423-435, 2017
Towards scalable and reliable capsule networks for challenging NLP applications
W Zhao, H Peng, S Eger, E Cambria, M Yang
arXiv preprint arXiv:1906.02829, 2019
Learning multi-grained aspect target sequence for Chinese sentiment analysis
H Peng, Y Ma, Y Li, E Cambria
Knowledge-Based Systems 148, 167-176, 2018
Disentangled variational auto-encoder for semi-supervised learning
Y Li, Q Pan, S Wang, H Peng, T Yang, E Cambria
Information Sciences 482, 73-85, 2019
Learning binary codes with neural collaborative filtering for efficient recommendation systems
Y Li, S Wang, Q Pan, H Peng, T Yang, E Cambria
Knowledge-Based Systems 172, 64-75, 2019
BabelSenticNet: A commonsense reasoning framework for multilingual sentiment analysis
D Vilares, H Peng, R Satapathy, E Cambria
2018 IEEE symposium series on computational intelligence (SSCI), 1292-1298, 2018
Phonetic-enriched text representation for Chinese sentiment analysis with reinforcement learning
H Peng, Y Ma, S Poria, Y Li, E Cambria
Information Fusion 70, 88-99, 2021
Radical-based hierarchical embeddings for chinese sentiment analysis at sentence level
H Peng, E Cambria, X Zou
Proceedings of FLAIRS, 347-352, 2017
End-to-end latent-variable task-oriented dialogue system with exact log-likelihood optimization
H Xu, H Peng, H Xie, E Cambria, L Zhou, W Zheng
World Wide Web 23 (3), 1989-2002, 2020
Cross-lingual aspect-based sentiment analysis with aspect term code-switching
W Zhang, R He, H Peng, L Bing, W Lam
Proceedings of the 2021 conference on empirical methods in natural language …, 2021
CSenticNet: a concept-level resource for sentiment analysis in Chinese language
H Peng, E Cambria
Proceedings of CICLing, 90-104, 2017
Fusing Phonetic Features and Chinese Character Representation for Sentiment Analysis
H Peng, S Poria, Y Li, E Cambria
International Conference on Computational Linguistics and Intelligent Text …, 2019
Linguistic-inspired Chinese sentiment analysis: from characters to radicals and phonetics
H Peng
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