A Scheme for Kinship Reasoning based on Ontology

With the rapid development of artificial intelligence and semantic networks, knowledge graphs have received extensive attention in various application domains. As a domain knowledge graph, a genealogical knowledge graph has significant research value in the family blood, family culture, and medical genetic analysis. However, as the identical relationship often has different names and complex relationships such as divorce, remarriage, and polygamy, the reasoning based on the genealogical knowledge graph is a challenging task. In response to this problem, we propose a scheme for kinship reasoning in the genealogical knowledge graph. First, based on real genealogical revision experiences, a character ontology framework in the genealogical knowledge graph is defined, and basic kinship reasoning rules are designed. Then, given different definitions of kinship in different surnames, the solution of custom reasoning rules is integrated into the reasoning framework. In addition, aiming at complex relationships in family trees, such as multiple generations of ancestors and multiple wives, a series of inference optimization methods are proposed. Finally, we implement this scheme in the Huapu system, and the experimental results conducted on a real genealogical dataset demonstrate the effectiveness and practicality of our proposed scheme.