融合专题知识和科技文献的科研知识图谱构建

本文为解决领域科技文献与专题价值的割裂问题提出深度融合科技文献、科研活动等科研对象与领域专题数据资源的图谱构建方法。通过主题词关联设计,构建包含期刊论文、期刊、科研机构、科研人员及专题实体类型的科研本体,选取机器学习专题构建科研知识图谱,并基于图数据库Neo4J进行图谱管理与查询验证。该专题科研知识图谱可以支持单实体/属性、多实体事实性问题的复杂图谱查询,有效揭示专题、科技文献的关联关系,具有较强的应用价值,可以为面向文献数据的智能知识服务提供新的思路和方向。

Construction of Scientific Knowledge Graph by Integrating Thematic Knowledge and Scientific Literature

In order to solve the problem of the separation of scientific literature and subject value,this paper proposes a method to construct knowledge graph that deeply integrates scientific literature,scientific activities and other scientific research objects and thematic data resources,and constructs including.A scientific ontology with journal article,journal,scientific research institution,and researcher as the main scientific research subjects,is developed through the subject association,and the subject of“machine learning”is selected to construct the thematic scientific knowledge graph,then the graph management and query verification are performed based on the graph database Neo4J.The thematic scientific knowledge graph constructed in this study can support complex graph query of factual issues with single-entity/property or multi-entity,and effectively reveal the relationship between thematic and scientific literature,which shows certain application value and can provide new ideas and directions for intelligent knowledge service.