Multi-grained Aspect Fusion for Review Response Generation-Reference-Cited by-同舟云学术

Multi-grained Aspect Fusion for Review Response Generation

Published:2023 Issue: Volume: Page:25-37
ISSN:0302-9743
Container-title:Artificial Neural Networks and Machine Learning – ICANN 2023
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Author:

Yuan Yun,Gong Chen,Kong Dexin,Yu Nan,Fu Guohong

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-44201-8_3

Reference28 articles.

1. Alturaief, N., Aljamaan, H., Baslyman, M.: Aware: aspect-based sentiment analysis dataset of apps reviews for requirements elicitation. In: 2021 36th IEEE/ACM International Conference on Automated Software Engineering Workshops (ASEW), pp. 211–218. IEEE (2021)

2. Cao, Y., Fard, F.H.: Pre-trained neural language models for automatic mobile app user feedback answer generation. CoRR abs/2202.02294 (2022). https://arxiv.org/abs/2202.02294

3. Chen, B., Liu, J., Maimaiti, M., Gao, X., Zhang, J.: Generating persuasive responses to customer reviews with multi-source prior knowledge in e-commerce. In: Hasan, M.A., Xiong, L. (eds.) Proceedings of the 31st ACM International Conference on Information & Knowledge Management, Atlanta, GA, USA, 17–21 October 2022, pp. 2994–3002. ACM (2022). https://doi.org/10.1145/3511808.3557122

4. Chen, H., Zhai, Z., Feng, F., Li, R., Wang, X.: Enhanced multi-channel graph convolutional network for aspect sentiment triplet extraction. In: Association for Computational Linguistics (ACL), 22–27 May 2022, pp. 2974–2985 (2022). https://doi.org/10.18653/v1/2022.acl-long.212

5. Cho, K., et al.: Learning phrase representations using RNN encoder-decoder for statistical machine translation. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP), pp. 1724–1734 (2014)