Reinforcement learning with actor-critic for knowledge graph reasoning

被引：1

作者：

Linli ZHANG ^{[1
,2
]}

Dewei LI ^{[1
,2
]}

Yugeng XI ^{[1
,2
]}

Shuai JIA ^{[1
,2
]}

机构：

[1] Department of Automation, Shanghai Jiao Tong University

来源：

ScienceChina(InformationSciences) | 2020年 / 63卷 / 06期

基金：

中国国家自然科学基金;

关键词：

Reinforcement learning with actor-critic for knowledge graph reasoning; MDP;

D O I：

暂无

中图分类号：

TP181 [自动推理、机器学习]; TP391.1 [文字信息处理];

学科分类号：

081104 ; 0812 ; 081203 ; 0835 ; 1405 ;

摘要：

Dear editor,In recent years, with the development of artificial intelligence and deep learning techniques, knowledge graph (KG) is receiving unprecedented attention. Essentially, KG is a semantic network, which stores massive information structured as entityrelation pairs in a graphical model. When the keywords or questions that users input are mapped

引用

页码：223 / 225

页数：3

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