1 |
WANG Y Q, HUANG M L, ZHU X Y, et al. Attention-based LSTM for aspect-level sentiment classification[C]//Proceedings of 2016 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, USA: Association for Computational Linguistics, 2016: 606-615.
|
2 |
KIM Y. Convolutional neural networks for sentence classification[C]//Proceedings of 2014 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, USA: Association for Computational Linguistics, 2014: 1746-1751.
|
3 |
TANG D Y, QIN B, LIU T. Aspect level sentiment classification with deep memory network[C]//Proceedings of 2016 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, USA: Association for Computational Linguistics, 2016: 214-224.
|
4 |
ZHANG M, QIAN T Y. Convolution over hierarchical syntactic and lexical graphs for aspect level sentiment analysis[C]//Proceedings of 2020 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, USA: Association for Computational Linguistics, 2020: 3540-3549.
|
5 |
ZHANG C, LI Q C, SONG D W. Aspect-based sentiment classification with aspect-specific graph convolutional networks[C]//Proceedings of 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing. Stroudsburg, USA: Association for Computational Linguistics, 2019: 4567-4577.
|
6 |
HUANG B X, CARLEY K. Syntax-aware aspect level sentiment classification with graph attention networks[C]//Proceedings of 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing. Stroudsburg, USA: Association for Computational Linguistics, 2019: 5469-5477.
|
7 |
SUN K, ZHANG R C, MENSAH S, et al. Aspect-level sentiment analysis via convolution over dependency tree[C]//Proceedings of 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing. Stroudsburg, USA: Association for Computational Linguistics, 2019: 5679-5688.
|
8 |
TAY Y, TUAN L A, HUI S C. Learning to attend via word-aspect associative fusion for aspect-based sentiment analysis[C]//Proceedings of AAAI Conference on Artificial Intelligence. [S. l. ]: AAAI Press, 2018: 5956-5963.
|
9 |
HOCHREITER S, SCHMIDHUBER J. Long short-term memory. Neural Computation, 1997, 9 (8): 1735- 1780.
doi: 10.1162/neco.1997.9.8.1735
|
10 |
|
11 |
田乔鑫, 孔韦韦, 滕金保, 等. 基于并行混合网络与注意力机制的文本情感分析模型. 计算机工程, 2022, 48 (8): 266- 273.
URL
|
|
TIAN Q X, KONG W W, TENG J B, et al. Text sentiment analysis model based on parallel hybrid network and attention mechanism. Computer Engineering, 2022, 48 (8): 266- 273.
URL
|
12 |
刘佳, 王潇, 王红旗. 基于LSTM的中文微博情感分析方法. 计算机工程与应用, 2020, 56 (13): 113- 119.
URL
|
|
LIU J, WANG X, WANG H Q. LSTM based sentiment analysis method for Chinese Weibo. Computer Engineering and Applications, 2020, 56 (13): 113- 119.
URL
|
13 |
DONG L, WEI F R, TAN C Q, et al. Adaptive recursive neural network for target-dependent Twitter sentiment classification[C]//Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics. Stroudsburg, USA: Association for Computational Linguistics, 2014: 49-54.
|
14 |
PONTIKI M, GALANIS D, PAVLOPOULOS J, et al. SemEval-2014 task 4: aspect based sentiment analysis[C]//Proceedings of the 8th International Workshop on Semantic Evaluation. Stroudsburg, USA: Association for Computational Linguistics, 2014: 27-35.
|
15 |
PONTIKI M, GALANIS D, PAPAGEORGIOU H, et al. SemEval-2015 task 12: aspect based sentiment analysis[C]//Proceedings of the 9th International Workshop on Semantic Evaluation. Stroudsburg, USA: Association for Computational Linguistics, 2015: 486-495.
|
16 |
PONTIKI M, GALANIS D, PAPAGEORGIOU H, et al. SemEval-2016 task 5: aspect based sentiment analysis[C]//Proceedings of the 8th International Workshop on Semantic Evaluation. San Diego, USA: [s. n. ], 2016: 19-30.
|
17 |
TANG D Y, QIN B, FENG X C, et al. Effective LSTMs for target-dependent sentiment classification[C]//Proceedings of the 26th International Conference on Computational Linguistics: Technical Papers. Osaka, Japan: [s. n. ], 2016: 3298-3307.
|
18 |
CHEN P, SUN Z Q, BING L D, et al. Recurrent attention network on memory for aspect sentiment analysis[C]//Proceedings of 2017 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, USA: Association for Computational Linguistics, 2017: 452-461.
|
19 |
HUANG B X, OU Y L, CARLEY K M. Aspect level sentiment classification with attention-over-attention neural networks[C]//Proceedings of International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction and Behavior Representation in Modeling and Simulation. Washington D. C., USA: IEEE Press, 2018: 197-206.
|
20 |
MA D H, LI S J, ZHANG X D, et al. Interactive attention networks for aspect-level sentiment classification[C]//Proceedings of the 26th International Joint Conference on Artificial Intelligence. Melbourne, Australia: International Joint Conferences on Artificial Intelligence Organization, 2017: 4068-4074.
|
21 |
CHEN C H, TENG Z Y, ZHANG Y. Inducing target-specific latent structures for aspect sentiment classification[C]//Proceedings of 2020 Conference on Empirical Methods in Natural Language Processing. Stroudsburg, USA: Association for Computational Linguistics, 2020: 5596-5607.
|