Quote Recommendation on QuoteR Classical Chinese 1.0 (test)
48.4MRRQuoteR
Evaluation Results
| Method | Links | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| QuoteR2022.02 | 48.4 | 49 | 3 | 146 | 422 | 41.67 | 60.78 | 79.38 | |
| QuoteR-Sememe2022.02 | 47.5 | 48.1 | 3 | 152 | 435 | 40.93 | 60.26 | 78.39 | |
| QuoteR-SimTrain2022.02 | 46.5 | 47 | 4 | 310 | 713 | 41.4 | 55.53 | 70.09 | |
| Transform2022.02 | 44.9 | 45.3 | 5 | 269 | 663 | 39.01 | 55.78 | 73.58 | |
| BERT-Sim2022.02 | 43.9 | 44.3 | 7 | 320 | 711 | 38.85 | 53.04 | 68.32 | |
| BERT-Cls2022.02 | 33 | 34.5 | 8 | 135 | 377 | 21.93 | 54.27 | 78.75 | |
| top-k RM2022.02 | 29.4 | 29.9 | 48 | 511 | 980 | 23.54 | 39.58 | 56.9 | |
| N-QRM2022.02 | 28.7 | 28.8 | 98 | 917 | 1,373 | 24.88 | 35.02 | 49.49 | |
| NNQR2022.02 | 27.2 | 27 | 41 | 310 | 620 | 22.03 | 36.59 | 60.63 | |
| QuoteR-ReTrain2022.02 | 26.5 | 26.9 | 17 | 184 | 450 | 17.87 | 43.56 | 72.89 | |
| LSTM2022.02 | 24.7 | 24.5 | 56 | 341 | 633 | 20.08 | 33.23 | 56.96 | |
| CRM2022.02 | 19.8 | 20.3 | 166 | 548 | 811 | 14.52 | 28.79 | 44.51 |