Knowledge Commons of Institute of Automation,CAS
Incorporating prior knowledge from counterfactuals into knowledge graph reasoning | |
Wang, Zikang1,2![]() ![]() ![]() | |
发表期刊 | Knowledge-Based Systems
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ISSN | 0950-7051 |
2021 | |
卷号 | 223期号:223页码:TBA |
通讯作者 | Li, Linjing(linjing.li@ia.ac.cn) |
摘要 | Knowledge graph reasoning aims to find the missing links in knowledge graphs and is an important fundamental task. Existing methods mostly reason end-to-end and ignore the prior knowledge in the knowledge graph. In this paper, we attempt to mine prior knowledge from the knowledge graph based on counterfactuals and to use the prior knowledge to enhance the model. Specifically, we begin by constructing counterfactuals to assign a weight for each relation as prior knowledge and then perform reasoning based on both prior knowledge and reinforcement learning. This approach combines the advantages of prior knowledge and neural networks. Experiments on three large datasets show that the prior knowledge extracted from counterfactuals is effective in improving the multi-hop reasoning model. Prior knowledge also has the advantage of being path-length independent, which mitigates the performance degradation in multi-hop reasoning when the reasoning path is excessively long. |
关键词 | knowledge graph multi-hop reasoning counterfactual |
DOI | 10.1016/j.knosys.2021.107035 |
关键词[WOS] | INFERENCE |
收录类别 | SCI |
语种 | 英语 |
资助项目 | National Key Research and Development Program of China[2020AAA0103405] ; National Natural Science Foundation of China[71621002] ; Strategic Priority Research Program of Chinese Academy of Sciences[XDA27030100] |
项目资助者 | National Key Research and Development Program of China ; National Natural Science Foundation of China ; Strategic Priority Research Program of Chinese Academy of Sciences |
WOS研究方向 | Computer Science |
WOS类目 | Computer Science, Artificial Intelligence |
WOS记录号 | WOS:000651271700013 |
出版者 | ELSEVIER |
七大方向——子方向分类 | 机器学习 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/44379 |
专题 | 多模态人工智能系统全国重点实验室_互联网大数据与信息安全 |
作者单位 | 1.State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences 2.Shenzhen Artificial Intelligence and Data Science Institute (Longhua) 3.Beijing Zhongke Wenge Science and Technology Co., Ltd. 4.School of Artificial Intelligence, University of Chinese Academy of Sciences |
第一作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Wang, Zikang,Li, Linjing,Zeng, Daniel,et al. Incorporating prior knowledge from counterfactuals into knowledge graph reasoning[J]. Knowledge-Based Systems,2021,223(223):TBA. |
APA | Wang, Zikang,Li, Linjing,Zeng, Daniel,&Wu, Xiaofei.(2021).Incorporating prior knowledge from counterfactuals into knowledge graph reasoning.Knowledge-Based Systems,223(223),TBA. |
MLA | Wang, Zikang,et al."Incorporating prior knowledge from counterfactuals into knowledge graph reasoning".Knowledge-Based Systems 223.223(2021):TBA. |
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