中文版 | English
题名

Zero-Shot Knowledge Graph Completion for Recommendation System

作者
通讯作者Tang, Ke
DOI
发表日期
2022
会议名称
23rd International Conference on Intelligent Data Engineering and Automated Learning (IDEAL)
ISSN
0302-9743
EISSN
1611-3349
ISBN
978-3-031-21752-4
会议录名称
卷号
13756
会议日期
NOV 24-26, 2022
会议地点
null,Manchester,ENGLAND
出版地
GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND
出版者
摘要
Knowledge graphs are structured representations of actual entities and relations. They are widely used to improve the performance of downstream tasks such as recommendation systems and semantic searching. Knowledge graph completion (KGC) is a technology for discovering the missing relations between the entities in a knowledge graph (KG). Existing methods leverage known relations on a KG to build a model to predict missing relations. Such methods implicitly require a substantial number of relations to be known in advance, which might not be available in practice. To cope with the cold-start scenario for KGC, i.e., no relation is known in advance, we propose a zero-shot approach in this paper. Our approach converts the KGC process to an optimization problem. It uses the Evolutionary Strategy (ES) algorithm to optimize a model used to complete the KG according to the performance of the recommendation system constructed based on the completed KG. Experiments on a movie dataset demonstrate that our approach can complete the KG in the cold-start scenario and improve the performance of the recommendation system built based on the completed KG.
关键词
学校署名
第一 ; 通讯
语种
英语
相关链接[来源记录]
收录类别
WOS研究方向
Computer Science
WOS类目
Computer Science, Artificial Intelligence ; Computer Science, Information Systems
WOS记录号
WOS:000904430900019
来源库
Web of Science
引用统计
被引频次[WOS]:0
成果类型会议论文
条目标识符http://kc.sustech.edu.cn/handle/2SGJ60CL/430693
专题工学院_计算机科学与工程系
作者单位
1.Southern Univ Sci & Technol, Dept Comp Sci & Engn, Guangdong Key Lab Brain Inspired Intelligent Comp, Shenzhen 518055, Peoples R China
2.Southern Univ Sci & Technol, Res Inst Trustworthy Autonomous Syst, Shenzhen 518055, Peoples R China
第一作者单位计算机科学与工程系
通讯作者单位计算机科学与工程系
第一作者的第一单位计算机科学与工程系
推荐引用方式
GB/T 7714
Wang, Zhiyuan,Chen, Cheng,Tang, Ke. Zero-Shot Knowledge Graph Completion for Recommendation System[C]. GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND:SPRINGER INTERNATIONAL PUBLISHING AG,2022.
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