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[1]常亮,张伟涛,古天龙,等.知识图谱的推荐系统综述[J].智能系统学报,2019,14(02):207-216.[doi:10.11992/tis.201805001]
 CHANG Liang,ZHANG Weitao,GU Tianlong,et al.Review of recommendation systems based on knowledge graph[J].CAAI Transactions on Intelligent Systems,2019,14(02):207-216.[doi:10.11992/tis.201805001]
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知识图谱的推荐系统综述(/HTML)
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《智能系统学报》[ISSN:1673-4785/CN:23-1538/TP]

卷:
第14卷
期数:
2019年02期
页码:
207-216
栏目:
出版日期:
2019-03-05

文章信息/Info

Title:
Review of recommendation systems based on knowledge graph
作者:
常亮 张伟涛 古天龙 孙文平 宾辰忠
桂林电子科技大学 广西可信软件重点实验室, 广西 桂林 541004
Author(s):
CHANG Liang ZHANG Weitao GU Tianlong SUN Wenping BIN Chenzhong
Guangxi Key Laboratory of Trusted Software, Guilin University of Electronic Technology, Guilin 541004, China
关键词:
知识图谱推荐系统本体开放链接数据库图嵌入网络表示学习相似度预测评分
Keywords:
knowledge graphrecommendation systemontologylinked open datagraph embeddingnetwork representation learningsimilarityprediction score
分类号:
TP301
DOI:
10.11992/tis.201805001
摘要:
如何为用户提供个性化推荐并提高推荐的准确度和用户满意度,是当前推荐系统研究面临的主要问题。知识图谱的出现为推荐系统的改进提供了新的途径。本文研究了知识图谱近年来在推荐系统中的应用情况,从基于本体的推荐生成、基于开放链接数据的推荐生成以及基于图嵌入的推荐生成3个方面对研究现状进行了综述。在此基础上,提出了基于知识图谱的推荐系统总体框架,分析了其中涉及的关键技术,并对目前存在的重点和难点问题进行了讨论,指出了下一步需要开展的研究工作。
Abstract:
In current research on recommendation systems, the provision of personalized recommendations to users and the improvement of the accuracy and user satisfaction of recommendations are main concerns. The emergence of knowledge graphs provides a new way to improve recommendation systems. The applications of knowledge graphs to recommendation systems in recent years are summarized in this paper, and the current status of the research is investigated in detail from three aspects:ontology-based recommendation generation, recommendation generation based on linked open data, and recommendation generation based on graph embedding. On this basis, this paper proposes the general framework of recommendation systems based on knowledge graph, analyzes the key technologies involved, discusses the existing key issues and difficulties, and indicates the further research work to be carried out.

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备注/Memo

备注/Memo:
收稿日期:2018-05-02。
基金项目:国家自然科学基金项目(61572146,U1501252,U1711263);广西创新驱动重大专项项目(AA17202024);广西自然科学基金项目(2016GXNSFDA380006).
作者简介:常亮,男,1980年生,教授,博士,中国计算机学会高级会员,主要研究方向为数据与知识工程、形式化方法、智能系统。主持并完成多项科研项目,其中国家自然科学基金项目1项、广西自然科学基金项目1项。发表学术论文70余篇,被SCI、EI收录60余篇。;张伟涛,男,1993年生,硕士研究生,主要研究方向为机器学习、推荐系统。;古天龙,男,1964年生,教授,博士生导师,博士,主要研究方向为形式化方法、知识工程与符号推理、协议工程与移动计算、可信泛在网络、嵌入式系统。主持国家863计划项目、国家自然科学基金、国防预研重点项目、国防预研基金等30余项。发表学术论文130余篇,被SCI、EI收录60余篇,出版学术著作3部。
通讯作者:宾辰忠.E-mail:binchenzhong@guet.edu.cn
更新日期/Last Update: 2019-04-25