Aspect-level sentiment analysis based on gradual machine learning-Reference-Cited by-同舟云学术

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Aspect-level sentiment analysis based on gradual machine learning

Published:2021-01 Issue: Volume:212 Page:106509
ISSN:0950-7051
Container-title:Knowledge-Based Systems
language:en
Short-container-title:Knowledge-Based Systems

Author:

Wang Yanyan,Chen Qun,Shen Jiquan,Hou Boyi,Ahmed Murtadha,Li Zhanhuai

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities, China

Natural Science Basic Research Plan in Shaanxi Province of China

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Management Information Systems,Software

Reference64 articles.

1. Survey on aspect-level sentiment analysis;Schouten;IEEE Trans. Knowl. Data Eng.,2016

2. W. Xue, T. Li, Aspect based sentiment analysis with gated convolutional networks, in: Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, ACL, Melbourne, Australia, 2018, pp. 2514–2523.

3. Y. Wang, M. Huang, X. Zhu, L. Zhao, Attention-based LSTM for aspect-level sentiment classification, in: Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, EMNLP, Austin, Texas, USA, 2016, pp. 606–615.

4. S. Ruder, P. Ghaffari, J.G. Breslin, A hierarchical model of reviews for aspect-based sentiment analysis, in: Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, EMNLP, Austin, Texas, USA, 2016, pp. 999–1005.

5. S. Kiritchenko, X. Zhu, C. Cherry, S. Mohammad, NRC-Canada-2014: detecting aspects and sentiment in customer reviews, in: Proceedings of the 8th International Workshop on Semantic Evaluation, SemEval@COLING, Dublin, Ireland, 2014, pp. 437–442.

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