Hybrid reasoning in knowledge graphs: Combing symbolic reasoning and statistical reasoning

Tracking #: 2200-3413

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Weizhuo Li
Guilin Qi
Qiu Ji

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Guest Editor 10-years SWJ

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Survey Article
Knowledge graph, as a backbone of many information systems, has been created to organize the rapidly growing knowledge in a semantical and visualized manner. Symbolic reasoning and statistical reasoning are current mainstream techniques that play important roles in knowledge completion, automatic schema constructing, complex question answering, explanation of AI. 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 problem settings and reasoning tasks, and introduce the key ideas of them. Finally, we re-examine the remaining research problems to be solved and outlook the future directions for hybrid reasoning in Knowledge graphs.
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