Publisher
Springer Science and Business Media LLC
Reference31 articles.
1. Abas, A., Elhenawy, I., Zidan, M., & Othman, M. (2021). BERT-CNN: A deep learning model for detecting emotions from text. Computers, Materials & Continua, 71(2), 2943–2961. https://www.techscience.com/cmc/v71n2/45793
2. Al-Omari, H., Abdullah, M. A., & Shaikh, S. (2020). EmoDet2: Emotion Detection in English Textual Dialogue using BERT and BiLSTM Models. 2020 11th International Conference on Information and Communication Systems (ICICS), 226–232. https://doi.org/10.1109/ICICS49469.2020.239539
3. Altrabsheh, N., Cocea, M., & Fallahkhair, S. (2014). Learning Sentiment from Students’ Feedback for Real-Time Interventions in Classrooms. In A. Bouchachia (Ed.), Adaptive and Intelligent Systems (Vol. 8779, pp. 40–49). Springer International Publishing. https://doi.org/10.1007/978-3-319-11298-5_5
4. Altrabsheh, N., Cocea, M., & Fallahkhair, S. (2015). Predicting Learning-Related Emotions from Students’ Textual Classroom Feedback via Twitter. In International Educational Data Mining Society. https://eric.ed.gov/?id=ED560882
5. Baqach, A., & Battou, A. (2021). Towards a user-oriented adaptive system based on sentiment analysis from text. E3S Web of Conferences, 297, 01010. https://doi.org/10.1051/e3sconf/202129701010
Cited by
3 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献