DAPath: Distance-aware knowledge graph reasoning based on deep reinforcement learning
文献类型：期刊论文
| 作者 | Tiwari, Prayag3; Zhu, Hongyin1 ; Pandey, Hari Mohan2
|
| 刊名 | NEURAL NETWORKS
 |
| 出版日期 | 2021-03-01 |
| 卷号 | 135页码:1-12 |
| 关键词 | Knowledge graph reasoning Reinforcement learning Graph self-attention GRU |
| ISSN号 | 0893-6080 |
| DOI | 10.1016/j.neunet.2020.11.012 |
| 通讯作者 | Tiwari, Prayag(prayag.tiwari@dei.unipd.it) ; Pandey, Hari Mohan(pandeyh@edgehill.ac.uk) |
| 英文摘要 | 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. |
| 资助项目 | European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie Grant[721321] |
| WOS研究方向 | Computer Science ; Neurosciences & Neurology |
| 语种 | 英语 |
| WOS记录号 | WOS:000610987500001 |
| 出版者 | PERGAMON-ELSEVIER SCIENCE LTD |
| 资助机构 | European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie Grant |
| 源URL | [http://ir.ia.ac.cn/handle/173211/43087]  |
| 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.Chinese Acad Sci, Inst Automat, Beijing, Peoples R China 2.Edge Hill Univ, Dept Comp Sci, Ormskirk L39 4QP, England 3.Univ Padua, Dept Informat Engn, Padua, Italy |
| 推荐引用方式 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. |
入库方式： OAI收割
来源：自动化研究所
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