Affiliations: [a] School of Computer Science and Engineering, Southeast University, Nanjing, China | [b] Key Laboratory of Computer Network and Information Integration (Southeast University), Ministry of Education, Nanjing, China. E-mails: [email protected], [email protected] | [c] School of Modern Posts and Institute of Modern Posts, Nanjing University of Posts and Telecommunications, Nanjing, China. E-mail: [email protected]
Abstract: Knowledge graphs (KGs) contain rich resources that represent human knowledge in the world. There are mainly two kinds of reasoning techniques in knowledge graphs, symbolic reasoning and statistical reasoning. However, both of them have their merits and limitations. Therefore, it is desirable to combine them to provide hybrid reasoning in a knowledge graph. In this paper, we present the first work on the survey of methods for hybrid reasoning in knowledge graphs. We categorize existing methods based on applications of reasoning techniques, and introduce the key ideas of them. Finally, we re-examine the remaining research problems to be solved and provide an outlook to future directions for hybrid reasoning in knowledge graphs.