Semantic-aware graph convolution network on multi-hop paths for link prediction |
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作者姓名: | 彭斐 CHEN Shudong QI Donglin YU Yong TONG Da |
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作者单位: | Institute of Microelectronics of the Chinese Academy of Sciences;University of Chinese Academy of Sciences |
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基金项目: | Supported by the National Natural Science Foundation of China (No. 61876144); |
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摘 要: | Knowledge graph(KG) link prediction aims to address the problem of missing multiple valid triples in KGs. Existing approaches either struggle to efficiently model the message passing process of multi-hop paths or lack transparency of model prediction principles. In this paper,a new graph convolutional network path semantic-aware graph convolution network(PSGCN) is proposed to achieve modeling tkhe semantic information of multi-hop paths. PSGCN first uses a random walk strategy to obtain all-hop ...
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