Research Article
[Retracted] HR Management Big Data Mining Based on Computational Intelligence and Deep Learning
Table 2
Experimental results of Cajon and comparison methods.
| Data set | Method | ROUGE | BLEU | Manual evaluation metrics | ROUGE-1 | ROUGE-2 | ROUGE-L | BLEU-1 (%) | BLEU-4 (%) | Fluency | Validity |
| T | Seq2Seq | 0.6389 | 0.4151 | 0.5996 | 37.32 | 16.22 | 3.66 | 3.58 | pGNet | 0.6413 | 0.4246 | 0.6061 | 38.14 | 16.75 | 3.70 | 3.61 | UniLM | 0.6167 | 0.3965 | 0.5863 | 34.64 | 12.29 | 3.52 | 3.14 | SAMA | 0.6004 | 0.3277 | 0.5455 | 39.30 | 15.07 | 3.47 | 3.52 | Cajon | 0.6531 | 0.4296 | 0.6077 | 41.81 | 19.41 | 3.73 | 3.81 |
| | Seq2Seq | 0.7236 | 0.5085 | 0.7138 | 32.02 | 7.28 | 3.63 | 3.34 | pGNet | 0.7421 | 0.5410 | 0.7331 | 32.72 | 8.28 | 3.67 | 3.41 | UniLM | 0.7542 | 0.5439 | 0.7452 | 31.43 | 6.42 | 3.46 | 3.28 | SAMA | 0.7160 | 0.4788 | 0.7074 | 34.76 | 9.00 | 3.55 | 3.49 | Cajon | 0.7522 | 0.5757 | 0.7531 | 36.46 | 10.84 | 3.78 | 3.74 |
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