參考文獻 |
[1] G. E. Hinton and R. R. Salakhutdinov, "Reducing the dimensionality of data with neural networks," science, vol. 313, no. 5786, pp. 504-507, 2006.
[2] A. Voulodimos, N. Doulamis, A. Doulamis, and E. Protopapadakis, "Deep learning for computer vision: A brief review," Computational intelligence and neuroscience, vol. 2018, 2018.
[3] J. L. Elman, "Finding structure in time," Cognitive science, vol. 14, no. 2, pp. 179-211, 1990.
[4] P. D. Turney, "Thumbs up or thumbs down? Semantic orientation applied to unsupervised classification of reviews," arXiv preprint cs/0212032, 2002.
[5] B. Snyder and R. Barzilay, "Multiple aspect ranking using the good grief algorithm," in Human Language Technologies 2007: The Conference of the North American Chapter of the Association for Computational Linguistics; Proceedings of the Main Conference, 2007, pp. 300-307.
[6] C. Strapparava and R. Mihalcea, "Learning to identify emotions in text," in Proceedings of the 2008 ACM symposium on Applied computing, 2008, pp. 1556-1560.
[7] J. Wiebe, T. Wilson, and C. Cardie, "Annotating expressions of opinions and emotions in language," Language resources and evaluation, vol. 39, no. 2-3, pp. 165-210, 2005.
[8] R. Socher et al., "Recursive deep models for semantic compositionality over a sentiment treebank," in Proceedings of the 2013 conference on empirical methods in natural language processing, 2013, pp. 1631-1642.
[9] N. Kalchbrenner, E. Grefenstette, and P. Blunsom, "A convolutional neural network for modelling sentences," arXiv preprint arXiv:1404.2188, 2014.
[10] K. S. Tai, R. Socher, and C. D. Manning, "Improved semantic representations from tree-structured long short-term memory networks," arXiv preprint arXiv:1503.00075, 2015.
[11] V. Yanulevskaya, J. C. van Gemert, K. Roth, A.-K. Herbold, N. Sebe, and J.-M. Geusebroek, "Emotional valence categorization using holistic image features," in 2008 15th IEEE international conference on Image Processing, 2008: IEEE, pp. 101-104.
[12] C. Xu, S. Cetintas, K. Lee, and L. Li, "Visual Sentiment Prediction with Deep Convolutional Neural Networks (2014)," arXiv preprint arXiv:1411.5731.
[13] Q. You, J. Luo, H. Jin, and J. Yang, "Robust image sentiment analysis using progressively trained and domain transferred deep networks," in Twenty-ninth AAAI conference on artificial intelligence, 2015.
[14] H.-B. Kang, "Affective content detection using HMMs," in Proceedings of the eleventh ACM international conference on Multimedia, 2003, pp. 259-262.
[15] X. Gibert, H. Li, and D. Doermann, "Sports video classification using HMMs," in 2003 International Conference on Multimedia and Expo. ICME′03. Proceedings (Cat. No. 03TH8698), 2003, vol. 2: IEEE, pp. II-345.
[16] B. Xu, Y. Fu, Y.-G. Jiang, B. Li, and L. Sigal, "Heterogeneous knowledge transfer in video emotion recognition, attribution and summarization," IEEE Transactions on Affective Computing, vol. 9, no. 2, pp. 255-270, 2016.
[17] Y. Fan, X. Lu, D. Li, and Y. Liu, "Video-based emotion recognition using CNN-RNN and C3D hybrid networks," in Proceedings of the 18th ACM International Conference on Multimodal Interaction, 2016, pp. 445-450.
[18] M. Hajar, "Using YouTube comments for text-based emotion recognition," Procedia Computer Science, vol. 83, pp. 292-299, 2016.
[19] P. Sarakit, T. Theeramunkong, C. Haruechaiyasak, and M. Okumura, "Classifying emotion in Thai youtube comments," in 2015 6th International Conference of Information and Communication Technology for Embedded Systems (IC-ICTES), 2015: IEEE, pp. 1-5.
[20] Y.-L. Chen, C.-L. Chang, and C.-S. Yeh, "Emotion classification of YouTube videos," Decision Support Systems, vol. 101, pp. 40-50, 2017.
[21] Z. S. Harris, "Distributional structure," in Papers in structural and transformational linguistics: Springer, 1970, pp. 775-794.
[22] J. R. Firth, "A synopsis of linguistic theory, 1930-1955," Studies in linguistic analysis, 1957.
[23] J. Savigny and A. Purwarianti, "Emotion classification on youtube comments using word embedding," in 2017 International Conference on Advanced Informatics, Concepts, Theory, and Applications (ICAICTA), 2017: IEEE, pp. 1-5.
[24] T. Mikolov, K. Chen, G. Corrado, and J. Dean, "Efficient estimation of word representations in vector space," arXiv preprint arXiv:1301.3781, 2013.
[25] Y. Kim, "Convolutional neural networks for sentence classification," arXiv preprint arXiv:1408.5882, 2014.
[26] S. Hochreiter and J. Schmidhuber, "Long short-term memory," Neural computation, vol. 9, no. 8, pp. 1735-1780, 1997.
[27] T. Fischer and C. Krauss, "Deep learning with long short-term memory networks for financial market predictions," European Journal of Operational Research, vol. 270, no. 2, pp. 654-669, 2018.
[28] D. Li and J. Qian, "Text sentiment analysis based on long short-term memory," in 2016 First IEEE International Conference on Computer Communication and the Internet (ICCCI), 2016: IEEE, pp. 471-475.
[29] A. Graves and J. Schmidhuber, "Framewise phoneme classification with bidirectional LSTM networks," in Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005., 2005, vol. 4: IEEE, pp. 2047-2052. |