Research Article
IARNN-Based Semantic-Containing Double-Level Embedding Bi-LSTM for Question-and-Answer Matching
Table 5
Top-1 accuracy and loss of each model.
| | Model | Train acc (%) | Train loss | Test acc (%) |
| 1 | BM25 | 44.80 | ∗∗∗ | 45.40 | 2 | Multiscale CNN | 66.53 | 1.95 | 64.67 | 3 | Attentive pooling | 85.33 | 1.7851 | 72.5256 | 4 | DMN | 75.24 | 0.92 | 74.38 | 5 | ESIM + ELMo | 80.37 | 1.15 | 77.15 | 6 | Multiview | 79.61 | 1.25 | 75.37 | 7 | CapsNet | 82.63 | 1.37 | 77.53 | 8 | SCDE-Bi-LSTM | 84.23 | 0.95 | 79.15 |
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