摘要
介绍了知识图谱产生的历史背景和典型的面向通用领域和学术信息服务领域的知识图谱;综述了知识图谱涉及的关键技术,包括知识抽取、知识融合以及知识加工;并以学者社交网络SCHOLAT为背景,给出学术知识图谱的模式设计,讨论知识图谱在学术信息服务领域中的应用意义.
The history of knowledge graph is introduced and several typical knowledge graphs for the general field and academic information services are introduced.The key technologies of knowledge graphs are surveyed,including knowledge extraction,knowledge integration and knowledge processing.Finally,the applications of knowledge graph in the field of academic information service,SCHOLAT,and its corresponding design pattern are presented.
作者
汤庸
陈国华
贺超波
彭博
TANG Yong;CHEN Guohua;HE Chaobo;PENG Bo(School of Computer Science, South China Normal University, Guangzhou 510631, China;Network Center, South China Normal University, Guangzhou 510631, China;School of Information Science and Technology, Zhongkai University of Agriculture and Engineering, Guangzhou 510225, China)
出处
《华南师范大学学报（自然科学版）》
CAS
北大核心
2018年第5期110-119,共10页
Journal of South China Normal University(Natural Science Edition)
基金
国家自然科学基金项目(61772211)
广东省科技计划项目(2017A040405057
2016B010124008)
广州市产学研协同创新重大专项(201704020203)
关键词
大数据
人工智能
知识图谱
学术信息服务
学者网
big data
artificial intelligence
knowledge graph
academic information service
SCHOLAT
