Table 4 Comparison of different models on two datasets
From: Joint contrastive learning and belief rule base for named entity recognition in cybersecurity
Model | Bridges et al. | OpenCS | ||||
|---|---|---|---|---|---|---|
P (%) | R (%) | F1 (%) | P (%) | R (%) | F1 (%) | |
Abdullah et al. (2018) | 88.92 | 82.27 | 85.47 | 79.35 | 71.59 | 75.27 |
Jie and Lu (2019) | 93.50 | 93.00 | 93.25 | 88.43 | 87.62 | 88.02 |
Zhou et al. (2021) | 91.94 | 90.79 | 91.36 | 85.64 | 84.19 | 84.90 |
Gao et al. (2021) | 94.14 | 93.69 | 93.92 | 89.62 | 88.36 | 88.99 |
Wu et al. (2022) | 91.88 | 93.18 | 92.53 | 80.71 | 78.92 | 79.80 |
Wang and Liu (2023) | 94.80 | 94.32 | 94.56 | 91.06 | 90.13 | 90.59 |
JCLB (Ours) | 95.16 | 94.30 | 94.73 | 91.59 | 90.68 | 91.13 |