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Knowledge Reasoning via Jointly Modeling Knowledge Graphs and Soft Rules

文献类型：期刊论文

作者Lan, Yinyu1,2; He, Shizhu1,2; Liu, Kang1,2; Zhao, Jun1,2
刊名APPLIED SCIENCES-BASEL
出版日期2023-10-01
卷号13期号:19页码:17
关键词distributed representation knowledge graph link prediction logical rule
DOI10.3390/app131910660
通讯作者He, Shizhu(shizhu.he@nlpr.ia.ac.cn)
英文摘要Knowledge graphs (KGs) play a crucial role in many applications, such as question answering, but incompleteness is an urgent issue for their broad application. Much research in knowledge graph completion (KGC) has been performed to resolve this issue. The methods of KGC can be classified into two major categories: rule-based reasoning and embedding-based reasoning. The former has high accuracy and good interpretability, but a major challenge is to obtain effective rules on large-scale KGs. The latter has good efficiency and scalability, but it relies heavily on data richness and cannot fully use domain knowledge in the form of logical rules. We propose a novel method that injects rules and learns representations iteratively to take full advantage of rules and embeddings. Specifically, we model the conclusions of rule groundings as 0-1 variables and use a rule confidence regularizer to remove the uncertainty of the conclusions. The proposed approach has the following advantages: (1) It combines the benefits of both rules and knowledge graph embeddings (KGEs) and achieves a good balance between efficiency and scalability. (2) It uses an iterative method to continuously improve KGEs and remove incorrect rule conclusions. Evaluations of two public datasets show that our method outperforms the current state-of-the-art methods, improving performance by 2.7% and 4.3% in mean reciprocal rank (MRR).
WOS研究方向Chemistry ; Engineering ; Materials Science ; Physics
语种英语
WOS记录号WOS:001086871600001
出版者MDPI
源URL[http://ir.ia.ac.cn/handle/173211/54310]  
专题复杂系统认知与决策实验室
模式识别国家重点实验室_自然语言处理
通讯作者He, Shizhu
作者单位1.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100190, Peoples R China
2.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 Lan, Yinyu,He, Shizhu,Liu, Kang,et al. Knowledge Reasoning via Jointly Modeling Knowledge Graphs and Soft Rules[J]. APPLIED SCIENCES-BASEL,2023,13(19):17.
APA Lan, Yinyu,He, Shizhu,Liu, Kang,&Zhao, Jun.(2023).Knowledge Reasoning via Jointly Modeling Knowledge Graphs and Soft Rules.APPLIED SCIENCES-BASEL,13(19),17.
MLA Lan, Yinyu,et al."Knowledge Reasoning via Jointly Modeling Knowledge Graphs and Soft Rules".APPLIED SCIENCES-BASEL 13.19(2023):17.

入库方式： OAI收割

来源：自动化研究所

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