基于多特征融合的中文文本分类研究*
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王艳,王胡燕,余本功
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Chinese Text Classification with Feature Fusion
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Wang Yan,Wang Huyan,Yu Bengong
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表4 多特征融合模型对比（计算机专利）
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Table 4 Comparison of Multi-Feature Fusion Models （Computer Data）
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| 数据集 | 模型 | Acc | P | R | F1 | | 计算机专利 | POS-BiGRUCNN | 57.3% | 59.4% | 58.1% | 60.0% | | PY-BiGRUCNN | 64.1% | 65.3% | 63.5% | 64.1% | | HZ-BiGRUCNN | 65.2% | 62.7% | 62.6% | 62.2% | | Word-BiGRUCNN | 76.1% | 76.9% | 76.2% | 76.5% | | POS-Word-BiGRUCNN | 78.1% | 77.5% | 77.1% | 77.3% | | PY-Word-BiGRUCNN | 79.1% | 78.8% | 78.5% | 77.5% | | HZ-Word-BiGRUCNN | 80.2% | 79.5% | 79.3% | 79.5% | | PY-POS-Word-BiGRUCNN | 81.3% | 80.3% | 78.6% | 79.4% | | HZ-POS-Word-BiGRUCNN | 81.2% | 81.3% | 80.5% | 80.9% | | PY-HZ-Word-BiGRUCNN | 82.2% | 82.3% | 81.9% | 80.9% | | PY-POS-HZ-Word-BiGRUCNN（本文） | 83.3% | 83.6% | 82.9% | 83.4% |
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