A survey on review summarization and sentiment classification
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Hardware and Architecture,Human-Computer Interaction,Information Systems,Software
Link
https://link.springer.com/content/pdf/10.1007/s10115-022-01728-y.pdf
Reference92 articles.
1. Wang L, Ling W (2016) Neural network-based abstract generation for opinions and arguments. In: Proceedings of the 2016 conference of the North American chapter of the association for computational linguistics: human language technologies. Association for Computational Linguistics, https://doi.org/10.18653/v1/n16-1007
2. Alsaqer AF, Sasi S (2017) Movie review summarization and sentiment analysis using rapidminer. In: 2017 International conference on networks and advances in computational technologies (NetACT). IEEE, https://doi.org/10.1109/netact.2017.8076790
3. Gerani S, Mehdad Y, Carenini G, Ng RT, Nejat B (2014) Abstractive summarization of product reviews using discourse structure. In: Proceedings of the 2014 conference on empirical methods in natural language processing (EMNLP). Association for Computational Linguistics, Doha, Qatar, pp 1602–1613. https://doi.org/10.3115/v1/D14-1168
4. Wu H, Gu Y, Sun S, Gu X (2016) Aspect-based opinion summarization with convolutional neural networks. In: 2016 International joint conference on neural networks (IJCNN). IEEE, https://doi.org/10.1109/ijcnn.2016.7727602
5. Chan, H.P., Chen, W., King, I.: A unified dual-view model for review summarization and sentiment classification with inconsistency loss. In: Proceedings of the 43rd international ACM SIGIR conference on research and development in information retrieval. ACM, (2020). https://doi.org/10.1145/3397271.3401039
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