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Semantic-aware graph convolution network on multi-hop paths for link prediction
作者姓名:彭斐  CHEN Shudong  QI Donglin  YU Yong  TONG Da
作者单位:Institute of Microelectronics of the Chinese Academy of Sciences;University of Chinese Academy of Sciences
基金项目:Supported by the National Natural Science Foundation of China (No. 61876144);
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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