Sentiment Analysis Model Based on the Word Structural Representation-Reference-Cited by-同舟云学术

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Sentiment Analysis Model Based on the Word Structural Representation

Published:2021 Issue: Volume: Page:170-178
ISSN:0302-9743
Container-title:Brain Informatics
language:
Short-container-title:

Author:

Bekmanova Gulmira^ORCID,Yergesh Banu^ORCID,Sharipbay Altynbek^ORCID

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-86993-9_16

Reference35 articles.

1. Franzoni, V., Milani, A., Nardi, D., Vallverdú, J.: Emotional machines: the next revolution. Web Intell. 17(1), 1–7 (2019). https://doi.org/10.3233/WEB-190395

2. Majumder, N., Poria, S., Hazarika, D., Mihalcea, R., Gelbukh, A., Cambria, E.: DialogueRNN: an attentive RNN for emotion detection in conversations. In: Proceedings of the AAAI Conference on Artificial Intelligence, Honolulu, pp. 6818–6825 (2019). https://doi.org/10.1609/aaai.v33i01.33016818

3. Lecture Notes in Computer Science;G Biondi,2017

4. Stappen, L., Baird, A., Cambria, E., Schuller, B.W., Cambria, E.: Sentiment analysis and topic recognition in video transcriptions. IEEE Intell. Syst. 36(2), 88–95 (2021). Article no. 9434455

5. Yang, D., Alsadoon, A., Prasad, P.W.C., Singh, A.K., Elchouemi, A.: An emotion recognition model based on facial recognition in virtual learning environment. Procedia Comput. Sci. 125, 2–10 (2018)

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