Hybrid reasoning in knowledge graphs: Combing symbolic reasoning and statistical reasoning
Weizhuo Li, Guilin Qi, Qiu Ji
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 com bine 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.