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A survey of text aspect-based sentiment classification
- Source :
- Journal of Hebei University of Science and Technology, Vol 41, Iss 6, Pp 518-527 (2020)
- Publication Year :
- 2020
- Publisher :
- Hebei University of Science and Technology, 2020.
-
Abstract
- With the development of deep learning, aspect-based sentiment classification has achieved a lot of results in a single field and a single language, but there is room for improvement in multi-fields. By summarizing up the methods of text aspect-based sentiment classification in recent years, the specific application scenarios of sentiment classification were introduced, and the commonly used data sets of aspect-based sentiment classification were categorized. The development of aspect-based sentiment classification were summarized and prospected, and further research can be carried out in the following areas: exploring methods based on graph neural networks to make up for the limitations of deep learning methods; learning to fuse multi-modal data to enrich the emotional information of a single text; developing more targeted research work on multilingual texts and low-resource languages.
Details
- Language :
- Chinese
- ISSN :
- 10081542
- Volume :
- 41
- Issue :
- 6
- Database :
- Directory of Open Access Journals
- Journal :
- Journal of Hebei University of Science and Technology
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.79f092f67154e30b6a0cdbaf9b2a931
- Document Type :
- article
- Full Text :
- https://doi.org/10.7535/hbkd.2020yx06006