基于深度学习的知识表示研究:网络视角*
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余传明,李浩男,王曼怡,黄婷婷,安璐
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Knowledge Representation Based on Deep Learning:Network Perspective
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Chuanming Yu,Haonan Li,Manyi Wang,Tingting Huang,Lu An
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表8 不同模型融合方式完成链接预测任务的部分实验结果(网络嵌入融合)
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Table 8 Partial Experimental Results of Link Prediction Tasks with Different Model Fusion Methods (Network Embedding Fusion)
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| | | Precision | Recall | F1 | AUC | 0.0 | 0.0 | 1.0 | 0.65 | 0.77 | 0.71 | 0.899 | 0.0 | 0.3 | 0.7 | 0.67 | 0.74 | 0.70 | 0.896 | 0.0 | 0.6 | 0.4 | 0.59 | 0.71 | 0.64 | 0.861 | 0.0 | 0.9 | 0.1 | 0.73 | 0.76 | 0.75 | 0.925 | 0.1 | 0.0 | 0.9 | 0.67 | 0.77 | 0.72 | 0.906 | 0.1 | 0.3 | 0.6 | 0.67 | 0.74 | 0.70 | 0.893 | 0.1 | 0.6 | 0.3 | 0.64 | 0.73 | 0.68 | 0.885 | 0.1 | 0.9 | 0.0 | 0.74 | 0.77 | 0.75 | 0.929 | 0.2 | 0.0 | 0.8 | 0.67 | 0.77 | 0.72 | 0.905 | 0.2 | 0.3 | 0.5 | 0.65 | 0.73 | 0.69 | 0.880 | 0.2 | 0.6 | 0.2 | 0.69 | 0.75 | 0.72 | 0.908 | 0.3 | 0.0 | 0.7 | 0.68 | 0.76 | 0.72 | 0.901 | 0.3 | 0.3 | 0.4 | 0.60 | 0.70 | 0.65 | 0.857 | 0.3 | 0.6 | 0.1 | 0.71 | 0.77 | 0.74 | 0.917 | 0.4 | 0.1 | 0.5 | 0.66 | 0.73 | 0.69 | 0.884 | 0.4 | 0.4 | 0.2 | 0.66 | 0.75 | 0.70 | 0.897 | 0.5 | 0.0 | 0.5 | 0.64 | 0.72 | 0.68 | 0.877 | 0.5 | 0.3 | 0.2 | 0.64 | 0.75 | 0.69 | 0.896 | 0.6 | 0.0 | 0.4 | 0.60 | 0.72 | 0.66 | 0.862 | 0.6 | 0.3 | 0.1 | 0.70 | 0.78 | 0.73 | 0.917 | 0.7 | 0.1 | 0.2 | 0.69 | 0.77 | 0.73 | 0.911 | 0.8 | 0.0 | 0.2 | 0.70 | 0.77 | 0.73 | 0.915 | 0.9 | 0.0 | 0.1 | 0.71 | 0.79 | 0.75 | 0.922 | 1.0 | 0.0 | 0.0 | 0.72 | 0.78 | 0.75 | 0.925 |
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