A Hybrid Approach with Machine Learning Towards Opinion Mining for Complex Textual Content
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-030-77442-4_55
Reference37 articles.
1. Bhatia, S., Chaudhary, P., Dey, N.: Opinion Mining in Information Retrieval. Springer, Singapore (2020). ISBN: 9789811550430, 9811550433
2. Gupta, N., Agrawal, R.: Extracting Knowledge from Opinion Mining. IGI-Global (2018). ISBN: 9781522561187, 1522561188
3. Kadiri, S.R., Alku, P.: Excitation features of speech for speaker-specific emotion detection. IEEE Access 8, 60382–60391 (2020). https://doi.org/10.1109/ACCESS.2020.2982954
4. Ke, Z., Sheng, J., Li, Z., Silamu, W., Guo, Q.: Knowledge-guided sentiment analysis via learning from natural language explanations. IEEE Access 9, 3570–3578 (2021). https://doi.org/10.1109/ACCESS.2020.3048088
5. Yang, J., Yang, J.: Aspect based sentiment analysis with self-attention and gated convolutional networks. In: 2020 IEEE 11th International Conference on Software Engineering and Service Science (ICSESS), Beijing, China, pp. 146–149 (2020). https://doi.org/10.1109/ICSESS49938.2020.9237640
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