Multi Criteria Decision Making Approach For Product Aspect Extraction And Ranking In Aspect-Based Sentiment Analysis
Identifying product aspects in customer reviews can have a great influence on both business strategies as well as on customers’ decisions. Presently, most research focuses on machine learning, statistical, and Natural Language Processing (NLP) techniques to identify the product aspects in customer r...
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| Format: | Thèse |
| Langue: | anglais |
| Publié: |
2018
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| Accès en ligne: | http://eprints.usm.my/43741/ |
| Abstract | Abstract here |
| Résumé: | Identifying product aspects in customer reviews can have a great influence on both business strategies as well as on customers’ decisions. Presently, most research focuses on machine learning, statistical, and Natural Language Processing (NLP) techniques to identify the product aspects in customer reviews. The challenge of this research is to formulate aspect identification as a decision-making problem. To this end, we propose a product aspect identification approach by combining multi-criteria decision-making (MCDM) with sentiment analysis. The suggested approach consists of two stages namely product aspect extraction and product aspect ranking. |
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