Research Article
A Knowledge Representation Method for Question Answering Service in Mobile Edge Computing Environment
Table 4
Comparison result with neural network methods on FB15K-237 and WN18RR.
| | FB15K−237 | WN18RR | MR | MRR | Hits@10 | Hits@3 | Hits@1 | MR | MRR | Hits@10 | Hits@3 | Hits@1 |
| CapsE | 303 | 0.523 | 0.593 | − | − | 719 | 0.415 | 0.56 | − | − | ConvKB | 216 | 0.289 | 0.471 | 0.327 | 0.198 | 1295 | 0.265 | 0.558 | 0.445 | 0.058 | ConvE | 245 | 0.312 | 0.497 | 0.341 | 0.225 | 4464 | 0.456 | 0.531 | 0.47 | 0.419 | SCAN | − | 0.35 | 0.54 | 0.39 | 0.26 | − | 0.47 | 0.54 | 0.48 | 0.43 | R-GCN | − | 0.249 | 0.417 | 0.264 | 0.151 | − | − | − | − | − |
| KRDGC | 158 | 0.527 | 0.662 | 0.563 | 0.46 | 1850 | 0.424 | 0.584 | 0.489 | 0.34 |
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