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: | Thesis |
| Language: | en |
| Published: |
2018
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| Online Access: | http://eprints.usm.my/43741/1/SAIF%20ADDEEN%20AHMAD%20ALI%20ALRABABAH.pdf http://eprints.usm.my/43741/ |
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| _version_ | 1834502896033464320 |
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| author | Alrababah, Saif Addeen Ahmad Ali |
| author_facet | Alrababah, Saif Addeen Ahmad Ali |
| author_sort | Alrababah, Saif Addeen Ahmad Ali |
| building | Hamzah Sendut Library |
| collection | Institutional Repository |
| content_provider | Universiti Sains Malaysia |
| content_source | USM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | 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. |
| format | Thesis |
| id | my.usm.eprints.43741 |
| institution | Universiti Sains Malaysia |
| language | en |
| publishDate | 2018 |
| record_format | eprints |
| spelling | my.usm.eprints.43741 http://eprints.usm.my/43741/ Multi Criteria Decision Making Approach For Product Aspect Extraction And Ranking In Aspect-Based Sentiment Analysis Alrababah, Saif Addeen Ahmad Ali QA75.5-76.95 Electronic computers. Computer science 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. 2018-04 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/43741/1/SAIF%20ADDEEN%20AHMAD%20ALI%20ALRABABAH.pdf Alrababah, Saif Addeen Ahmad Ali (2018) Multi Criteria Decision Making Approach For Product Aspect Extraction And Ranking In Aspect-Based Sentiment Analysis. PhD thesis, Universiti Sains Malaysia. |
| spellingShingle | QA75.5-76.95 Electronic computers. Computer science Alrababah, Saif Addeen Ahmad Ali Multi Criteria Decision Making Approach For Product Aspect Extraction And Ranking In Aspect-Based Sentiment Analysis |
| title | Multi Criteria Decision Making Approach For Product Aspect Extraction And Ranking In Aspect-Based Sentiment Analysis |
| title_full | Multi Criteria Decision Making Approach For Product Aspect Extraction And Ranking In Aspect-Based Sentiment Analysis |
| title_fullStr | Multi Criteria Decision Making Approach For Product Aspect Extraction And Ranking In Aspect-Based Sentiment Analysis |
| title_full_unstemmed | Multi Criteria Decision Making Approach For Product Aspect Extraction And Ranking In Aspect-Based Sentiment Analysis |
| title_short | Multi Criteria Decision Making Approach For Product Aspect Extraction And Ranking In Aspect-Based Sentiment Analysis |
| title_sort | multi criteria decision making approach for product aspect extraction and ranking in aspect-based sentiment analysis |
| topic | QA75.5-76.95 Electronic computers. Computer science |
| url | http://eprints.usm.my/43741/1/SAIF%20ADDEEN%20AHMAD%20ALI%20ALRABABAH.pdf http://eprints.usm.my/43741/ |
| url_provider | http://eprints.usm.my/ |