Research Article
Opinion Mining from Online User Reviews Using Fuzzy Linguistic Hedges
Table 3
Accuracy of feature-based opinion classification using linguistic hedges.
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Dataset | Approaches to feature-based classification using linguistic hedges |
Approach 1: valence points adjustment approach |
Approach 2: Vo and Ock's fuzzy adjustment functions | Approach 3: our proposed method | Binary classification accuracy (%) | Fine-grained classification accuracy (%) | Binary classification accuracy (%) | Fine-grained classification accuracy (%) | Binary classification accuracy (%) | Fine-grained classification accuracy (%) |
| Tablets | 80.87 | 71.62 | 87.28 | 79.73 | 90.16 | 87.45 | E-book readers | 76.21 | 65.89 | 77.37 | 72.95 | 85.44 | 82.72 | Smartphones | 88.32 | 74.36 | 89.16 | 83.93 | 92.56 | 89.95 | Laptops | 84.26 | 73.32 | 86.67 | 79.65 | 88.67 | 85.77 | Average | 82.42 | 71.30 | 85.12 | 79.07 | 89.21 | 86.47 |
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