Table 5.
Evaluation Results on the WhiteText Corpus of the proposed Linguistically Motivated Approach and the previous related studies.
| Precision (%) | Recall (%) | F-Measure (%) | |
|---|---|---|---|
| Linguistically Motivated Approach—2nd dataset (1828 abstracts) | 76.94 | 14.59 | 24.53 |
| (French et al., 2015)—2nd dataset (1828 abstracts) | |||
| Shallow Linguistic Kernel (SLK) | 51.00 | 67.00 | 57.92 |
| Linguistically Motivated Approach—1st dataset (1377 abstracts) | 75.60 | 17.31 | 28.17 |
| (French et al., 2012)—1st dataset (1377 abstracts) | |||
| Shallow Linguistic Kernel (SLK) | 50.30 | 71.10 | 58.30 |
| (Richardet et al., 2015)—1st dataset (1377 abstracts) | |||
| Kernel (SLK) | 60.00 | 68.00 | 64.00 |
| Ruta Rules | 72.00 | 12.00 | 21.00 |
| Filter–Kernel | 66.00 | 19.00 | 29.00 |
| Kernel–Rules | 81.00 | 10.00 | 18.00 |
| Filter–Kernel–Rules | 82.00 | 7.00 | 12.00 |