| 摘 要: 近年来，知识图谱已逐渐从传统的知识分析应用发展到对社会实体及关系的应用。本文针对知识图谱的人员关系应用研究，以疫情病例人员关系为例获取数据源，通过数据预处理、知识抽取等方式构建病例人员关系三元组，采用Protégé工具构建本体，并导入Neo4j图形数据库中进行存储，最后构建病例人员关系知识图谱，实现可视化查询病例人员及关系信息。同时，运用Neo4j的中心度算法和度中心性算法分析所有病例人员的感染力和接触人数，从而发现病例中感染力较强、接触人数较多的人员，为未来疾病防控体系的建立提供了参考，对病例人员关系的研究分析也具有一定的实用价值。 |
| 关键词: 知识图谱；图数据库；Neo4j；关系分析 |
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中图分类号: TP391
文献标识码: A
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| Construction and Application of Personnel Relationship Knowledge Graph based on Neo4j |
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LU Feng
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(Henan Police College, Zhengzhou 450046, China)
279840745@qq.com
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| Abstract: In recent years, knowledge graph has been gradually applied from traditional knowledge analysis to the application of social entities and their relationships. This paper proposes to study the application of knowledge graph to personnel relationship, and the data source is obtained by taking the epidemic case-person relationship as an example. The case-person relationship triplet is constructed by data preprocessing and knowledge extraction, etc., and the Protégé tool is used to construct the ontology, which is imported into Neo4j graphic database for storage. Finally, a knowledge graph of case-person relationship is built, realizing the visual query of case personnel and their relationship information. Meanwhile, the centrality algorithm and the degree centrality algorithm of Neo4j are used to analyze the infectivity and contact number of all case persons, so as to find out among the cases, persons with strong infectivity and more contacts. It provides a reference for the establishment of the future disease prevention and control system, and also has certain practical value for the research and analysis of the case-person relationship. |
| Keywords: knowledge graph; graph database; Neo4j; relational analysis |
