Research Article
Abstractive Arabic Text Summarization Based on Deep Learning
Table 5
Performance comparisons of the proposed system by using AraBERT preprocess and without using it.
| Dataset | Preprocess | ROUGE-1 | ROUGE-2 | ROUGE-L | BLEU | Precision | Recall | F1 | Precision | Recall | F1 | Precision | Recall | F1 |
| AHS | With AraBERT | 54.95 | 50.48 | 51.49 | 13.1 | 12.01 | 12.27 | 37.84 | 35.19 | 34.37 | 0.41 | Without AraBERT | 52.44 | 49.5 | 49.79 | 12.23 | 11.5 | 11.6 | 36.12 | 34.66 | 33.22 | 0.39 |
| AMN | With AraBERT | 48.15 | 42.65 | 44.28 | 19.46 | 17.93 | 18.35 | 35.48 | 32.86 | 32.46 | 0.41 | Without AraBERT | 45.9 | 38.3 | 40.7 | 17.63 | 15.53 | 16.18 | 33.19 | 29.21 | 29.15 | 0.36 |
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The highest result is given in bold.
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