Hierarchical Multihop Reasoning on Knowledge Graphs
Wang, Zikang1,2; Li, Linjing1,2,3; Zeng, Daniel Dajun1,2,3
Source PublicationIEEE INTELLIGENT SYSTEMS
ISSN1541-1672
2022
Volume37Issue:1Pages:71-78
Corresponding AuthorWang, Zikang(wangzikang2016@ia.ac.cn)
AbstractMultihop knowledge reasoning aims to find missing entities for incomplete triples by finding paths on knowledge graphs. It is a fundamental and important task. In this article, we devise a hierarchical reinforcement learning algorithm to model the reasoning process more effectively. Unlike existing methods directly reason on entities and relations, we adopt a high-level reasoning layer to deal with abstract concepts, which guides the reasoning process conducted at the low level for concrete entities and relations. Our approach yields competitive results on link prediction on both NELL-995 and FB15k-237 datasets. The comparison to baselines also demonstrates the effectiveness of the hierarchical structure.
DOI10.1109/MIS.2021.3095055
Indexed BySCI
Language英语
Funding ProjectNational 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]
Funding OrganizationNational Key Research and Development Program of China ; National Natural Science Foundation of China ; Strategic Priority Research Program of Chinese Academy of Sciences
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS IDWOS:000792916700009
PublisherIEEE COMPUTER SOC
Citation statistics
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/49417
Collection复杂系统管理与控制国家重点实验室_互联网大数据与信息安全
Corresponding AuthorWang, Zikang
Affiliation1.Chinese Acad Sci, Inst Automat, Beijing 100864, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
3.4Data Sci Inst Longhua, Shenzhen 518129, Peoples R China
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Corresponding Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Wang, Zikang,Li, Linjing,Zeng, Daniel Dajun. Hierarchical Multihop Reasoning on Knowledge Graphs[J]. IEEE INTELLIGENT SYSTEMS,2022,37(1):71-78.
APA Wang, Zikang,Li, Linjing,&Zeng, Daniel Dajun.(2022).Hierarchical Multihop Reasoning on Knowledge Graphs.IEEE INTELLIGENT SYSTEMS,37(1),71-78.
MLA Wang, Zikang,et al."Hierarchical Multihop Reasoning on Knowledge Graphs".IEEE INTELLIGENT SYSTEMS 37.1(2022):71-78.
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