KFEA: Fine-Grained Review Analysis Using BERT with Attention: A Categorical and Rating-Based Approach-Reference-Cited by-同舟云学术

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KFEA: Fine-Grained Review Analysis Using BERT with Attention: A Categorical and Rating-Based Approach

Published:2023 Issue: Volume: Page:260-274
ISSN:0302-9743
Container-title:Advanced Data Mining and Applications
language:
Short-container-title:

Author:

Huang Liting,Yang Yongyue,Tang Xingli,Zhou Hui,Ye Chunyang

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-46661-8_18

Reference28 articles.

1. Alamoudi, E.S., Alghamdi, N.S.: Sentiment classification and aspect-based sentiment analysis on yelp reviews using deep learning and word embeddings. J. Decis. Syst. 30, 259–281 (2021)

2. Cambria, E., Schuller, B., Xia, Y., Havasi, C.: New avenues in opinion mining and sentiment analysis. IEEE Intell. Syst. 28, 15–21 (2013)

3. Chatterjee, S., Goyal, D., Prakash, A., Sharma, J.: Exploring healthcare/health-product ecommerce satisfaction: a text mining and machine learning application. J. Bus. Res. 131, 815–825 (2021)

4. Cheng, X., Zhou, M.: Study on effect of ewom: a literature review and suggestions for future research. In: 2010 International Conference on Management and Service Science, pp. 1–4 (2010)

5. Dai, H., Lai, P.T., Chang, Y.C., Tsai, R.T.H.: Enhancing of chemical compound and drug name recognition using representative tag scheme and fine-grained tokenization. J. Cheminform, 7, S14–S14 (2015)

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