An innovative word embedded and optimization based hybrid artificial intelligence approach for aspect-based sentiment analysis of app and cellphone reviews

Author:

Devi N. Lakshmi,Anilkumar B.,Sowjanya A. Mary,Kotagiri Srividya

Publisher

Springer Science and Business Media LLC

Reference44 articles.

1. Yang L et al (2020) Sentiment analysis for E-commerce product reviews in Chinese based on sentiment lexicon and deep learning. IEEE Access 8:23522–23530

2. Xu G et al (2019) Sentiment analysis of comment texts based on BiLSTM. IEEE Access 7:51522–51532

3. Jiang Q, Chen L, Xu R, Ao X, Yang M (2019) A challenge dataset and effective models for aspect-based sentiment analysis. In: Proceedings of the 2019 conference on empirical methods in natural language processing and the 9th international joint conference on natural language processing (EMNLP-IJCNLP) (pp. 6280–6285) Hong Kong, China. Association for Computational Linguistics

4. D’Aniello G, Gaeta M, La Rocca I (2022) KnowMIS-ABSA: an overview and a reference model for applications of sentiment analysis and aspect-based sentiment analysis. Artif Intell Rev 55:5543–5574

5. Tian Y, Chen G, Song Y (2021) Aspect-based sentiment analysis with type-aware graph convolutional networks and layer ensemble. In: Proceedings of the 2021 conference of the North American chapter of the association for computational linguistics: human language technologies. Association for Computational Linguistics, pp 2910–2922

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