Research Article
A Depth Evidence Score Fusion Algorithm for Chinese Medical Intelligence Question Answering System
Table 3
Accuracy comparison of different system algorithms.
| System | Feature algorithm (%) | Precision (%) | Recall (%) | F-measure (%) |
| WSESA | PTM | 73.7 | 91.8 | 81.7 | S-B | 81.4 | 90.4 | 85.7 | TA | 75.3 | 84.9 | 79.8 | LFACS | 86.2 | 57.5 | 69.0 |
| PFEGA | Lexical features | 57.2 | 62.4 | 59.68 | Syntactic features | 63.7 | 79.8 | 70.84 | Semantic features | 71.8 | 84.6 | 77.67 | Structural features | 68.6 | 82.2 | 74.78 |
| DTSFA | Frequency | 76.8 | 92.7 | 84.0 | Order | 74.5 | 82.3 | 78.21 | TF-IDF | 83.4 | 75.1 | 79.03 | Syntax | 85.8 | 88.7 | 87.23 | Structure | 72.3 | 83.4 | 77.46 | Semantics | 80.6 | 77.2 | 78.86 |
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