A Framework of Customer Review Analysis Using the Aspect-Based Opinion Mining Approach
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Abstract (arXiv)
Opinion mining is the branch of computation that deals with opinions, appraisals, attitudes, and emotions of people and their different aspects. This field has attracted substantial research interest in recent years. Aspect-level (called aspect-based opinion mining) is often desired in practical applications as it provides detailed opinions or sentiments about different aspects of entities and entities themselves, which are usually required for action. Aspect extraction and entity extraction are thus two core tasks of aspect-based opinion mining. his paper has presented a framework of aspect-based opinion mining based on the concept of transfer learning. on real-world customer reviews available on the Amazon website. The model has yielded quite satisfactory results in its task of aspect-based opinion mining.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 6 of its 18 references that are in the map. First posted on arXiv 20 Dec 2022.
Builds on
6 of 18 references.
References · 6
- 2021Learn from Syntax: Improving Pair-wise Aspect and Opinion Terms Extractionwith Rich Syntactic Knowledgecited by 31
- 2021CLASSIC: Continual and Contrastive Learning of Aspect Sentiment Classification Taskscited by 29
- 2020A Simple and Effective Self-Supervised Contrastive Learning Framework for Aspect Detectioncited by 13
- 2021Graph Ensemble Learning over Multiple Dependency Trees for Aspect-level Sentiment Classificationcited by 13
- 2021Eliminating Sentiment Bias for Aspect-Level Sentiment Classification with Unsupervised Opinion Extractioncited by 11
- 2019Earlier Attention? Aspect-Aware LSTM for Aspect-Based Sentiment Analysiscited by 9
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Citing papers per year: 2023: 1.
1 paper.