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DAPath: Distance-aware knowledge graph reasoning based on deep reinforcement learning
Tiwari, Prayag1; Zhu, Hongyin2; Pandey, Hari Mohan3
发表期刊NEURAL NETWORKS
ISSN0893-6080
2021-03-01
卷号135页码:1-12
通讯作者Tiwari, Prayag(prayag.tiwari@dei.unipd.it) ; Pandey, Hari Mohan(pandeyh@edgehill.ac.uk)
摘要Knowledge graph reasoning aims to find reasoning paths for relations over incomplete knowledge graphs (KG). Prior works may not take into account that the rewards for each position (vertex in the graph) may be different. We propose the distance-aware reward in the reinforcement learning framework to assign different rewards for different positions. We observe that KG embeddings are learned from independent triples and therefore cannot fully cover the information described in the local neighborhood. To this effect, we integrate a graph self-attention (GSA) mechanism to capture more comprehensive entity information from the neighboring entities and relations. To let the model remember the path, we incorporate the GSA mechanism with GRU to consider the memory of relations in the path. Our approach can train the agent in one-pass, thus eliminating the pre-training or finetuning process, which significantly reduces the problem complexity. Experimental results demonstrate the effectiveness of our method. We found that our model can mine more balanced paths for each relation. (c) 2020 Elsevier Ltd. All rights reserved.
关键词Knowledge graph reasoning Reinforcement learning Graph self-attention GRU
DOI10.1016/j.neunet.2020.11.012
收录类别SCI
语种英语
资助项目European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie Grant[721321]
项目资助者European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie Grant
WOS研究方向Computer Science ; Neurosciences & Neurology
WOS类目Computer Science, Artificial Intelligence ; Neurosciences
WOS记录号WOS:000610987500001
出版者PERGAMON-ELSEVIER SCIENCE LTD
引用统计
被引频次:29[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/43088
专题类脑智能研究中心_类脑认知计算
通讯作者Tiwari, Prayag; Pandey, Hari Mohan
作者单位1.Univ Padua, Dept Informat Engn, Padua, Italy
2.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China
3.Edge Hill Univ, Dept Comp Sci, Ormskirk L39 4QP, England
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GB/T 7714
Tiwari, Prayag,Zhu, Hongyin,Pandey, Hari Mohan. DAPath: Distance-aware knowledge graph reasoning based on deep reinforcement learning[J]. NEURAL NETWORKS,2021,135:1-12.
APA Tiwari, Prayag,Zhu, Hongyin,&Pandey, Hari Mohan.(2021).DAPath: Distance-aware knowledge graph reasoning based on deep reinforcement learning.NEURAL NETWORKS,135,1-12.
MLA Tiwari, Prayag,et al."DAPath: Distance-aware knowledge graph reasoning based on deep reinforcement learning".NEURAL NETWORKS 135(2021):1-12.
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