[1] 牛耘, 潘明慧, 魏欧, 等.基于词典的中文微博情绪识别[J].计算机科学, 2014, 41(9):253-258, 289. NIU Y, PAN M H, WEI O, et al.Emotion analysis of Chinese microblogs using lexicon-based approach[J].Computer Science, 2014, 41(9):253-258, 289.(in Chinese) [2] 周锦峰, 叶施仁, 王晖.基于深度卷积神经网络模型的文本情感分类[J].计算机工程, 2019, 45(3):300-308. ZHOU J F, YE S R, WANG H.Text sentiment classification based on deep convolutional neural network model[J].Computer Engineering, 2019, 45(3):300-308.(in Chinese) [3] 蔡林森, 彭超, 陈思远, 等.基于多样化特征卷积神经网络的情感分析[J].计算机工程, 2019, 45(4):169-174, 180. CAI L S, PENG C, CHEN S Y, et al.Sentiment analysis based on multiple features convolutional neural networks[J].Computer Engineering, 2019, 45(4):169-174, 180.(in Chinese) [4] HAZARIKA D, PORIA S, ZADEH A, et al.Conversational memory network for emotion recognition in dyadic dialogue videos[C]//Proceedings of the Conference of the North American Chapter of the Association for Computational Linguistics.[S.l.]:ACL, 2018:2122-2132. [5] MICHAEL W M, DACHER K.How emotions work:the social functions of emotional expression in negotiations[J].Research in Organizational Behavior, 2000, 22:1-50. [6] LIU F, MAITLIS S.Emotional dynamics and strategizing processes:a study of strategic conversations in top team meetings[J].Journal of Management Studies, 2014, 51(2):202-234. [7] PORIA S, CHATURVEDI I, CAMBRIA E, et al.Convolutional MKL based multimodal emotion recognition and sentiment analysis[C]//Proceedings of 2016 IEEE International Conference on Data Mining.Washington D.C., USA:IEEE Press, 2016:439-448. [8] PORIA S, CAMBRIA E, HAZARIKA D, et al.Context-dependent sentiment analysis in user-generated videos[C]//Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics.[S.l.]:ACL, 2017:873-883. [9] HAZARIKA D, PORIA S, MIHALCEA R, et al.ICON:interactive conversational memory network for multimodal emotion detection[C]//Proceedings of 2018 Conference on Empirical Methods in Natural Language Processing.Washington D.C., USA:IEEE Press, 2018:2594-2604. [10] HAZARIKA D, PORIA S, ZIMMERMANN R, et al.Emotion recognition in conversations with transfer learning from generative conversation modeling[EB/OL].[2020-11-02].https://arxiv.org/pdf/1910.04980v1.pdf. [11] MAJUMDER N, PORIA S, HAZARIKA D, et al.DialogueRNN:an attentive RNN for emotion detection in conversations[C]//Proceedings of AAAI Conference on Artificial Intelligence.[S.l.]:AAAI Press, 2019:6818-6825. [12] JIN X, YU J, DING Z, et al.Hierarchical multimodal transformer with localness and speaker aware attention for emotion recognition in conversations[C]//Proceedings of CCF International Conference on Natural Language Processing and Chinese Computing.Washington D.C., USA:IEEE Press, 2020:41-53. [13] 高玮军, 杨杰, 张春霞, 等.基于AT-DPCNN模型的情感分析研究[J].计算机工程, 2020, 46(11):53-60. GAO W J, YANG J, ZHANG C X, et al.Sentiment analysis reserach based on AT-DPCNN model[J].Computer Engineering, 2020, 46(11):53-60.(in Chinese) [14] PORIA S, MAJUMDER N, MIHALCEA R, et al.Emotion recognition in conversation:research challenges, datasets, and recent advances[J].IEEE Access, 2019, 7:100943-100953. [15] ZHANG D, WU L Q, SUN C L, et al.Modeling both context-and speaker-sensitive dependence for emotion detection in multi-speaker conversations[C]//Proceedings of the 28th International Joint Conference on Artificial Intelligence.Washington D.C., USA:IEEE Press, 2019:5415-5421. [16] ZHONG P X, WANG D, MIAO C Y.Knowledge-enriched transformer for emotion detection in textual conversations[C]//Proceedings of Conference on Empirical Methods in Natural Language Processing.Washington D.C., USA:IEEE Press, 2019:165-177. [17] XU X, RUAN Z, YANG L.Facial expression recognition based on graph neural network[C]//Proceedings of 2020 IEEE International Conference on Image, Vision and Computing.Washington D.C., USA:IEEE Press, 2020:211-214. [18] WANG Z, TONG Y, HENG X.Phase-locking value based graph convolutional neural networks for emotion recognition[J].IEEE Access, 2019, 7:93711-93722. [19] SONG T, ZHENG W, SONG P, et al.EEG emotion recognition using dynamical graph convolutional neural networks[J].IEEE Transactions on Affective Computing, 2020, 11(3):532-541. [20] LO L, XIE H X, SHUAI H H, et al.MER-GCN:micro expression recognition based on relation modeling with graph convolutional network[EB/OL].[2020-11-02].https://arxiv.org/pdf/2004.08915.pdf. [21] GHOSAL D, MAJUMDER N, PORIA S, et al.DialogueGCN:a graph convolutional neural network for emotion recognition in conversation[EB/OL].[2020-11-02].https://aclanthology.org/D19-1015.pdf. [22] KIPF T N, WELLING M.Semi-supervised classification with graph convolutional networks[EB/OL].[2020-11-02].https://arxiv.org/pdf/1609.02907.pdf. [23] SCHLICHTKRULL M, KIPF T N, BLOEM P, et al.Modeling relational data with graph convolutional networks[C]//Proceedings of European Semantic Web Conference.Berlin, Germany:Springer, 2018:593-607. [24] CARLOS B, MURTAZA B, CHI-CHUN L, et al.IEMOCAP:interactive emotional dyadic motion capture database[J].Language Resources and Evaluation, 2008, 42(4):335-359. [25] KINGMA D P, JIMMY B.Adam:a method for stochastic optimization[EB/OL].[2020-11-02].https://arxiv.org/pdf/1412.6980.pdf. [26] SRIVASTAVA N, HINTON G, KRIZHEVSKY A, et al.Dropout:a simple way to prevent neural networks from overfitting[J].The Journal of Machine Learning Research, 2014, 15(1):1929-1958. [27] HOCHREITER S, SCHMIDHUBER J.Long short-term memory[J].Neural Computation, 1997, 9(8):1735-1780. [28] CHUNG J, GULCEHRE C, CHO K H, et al.Empirical evaluation of gated recurrent neural networks on sequence modeling[EB/OL].[2020-11-02].https://arxiv.org/pdf/1412.3555v1.pdf. |