河流污染知识图谱的构建及应用

Construction and Application of Knowledge Graph of River Pollution

针对目前河流污染事件中相关元素关联性不强的问题,基于知识图谱在知识表示上的优势,构建河流污染知识图谱并进行应用。首先,对知识图谱的模式层和数据层的构建方法进行梳理;然后,以木兰溪流域为例,采用自顶向下的方式构建河流污染知识图谱的模式层,运用结构化数据和非结构化数据抽取技术构建河流污染知识图谱的数据层,并基于Neo4j图形数据库对知识进行存储和应用;最后,利用该知识图谱实现了木兰溪流域污染事件的快速溯源。实验表明,该河流污染知识图谱的构建有效解决了水污染相关数据分散、关联性不强等问题,对水污染事件的快速溯源具有一定的应用价值。

In response to the problem of weak correlation between related elements in current river pollution incidents,a river pollution knowledge graph is constructed and applied based on the advantages of knowledge representation in knowledge graphs.Firstly,the construction methods of the pattern layer and data layer of the knowledge graph are sorted out.Then,take the Mulanxi River Basin for example,the pattern layer of the river pollution knowledge graph is constructed in a top-down manner,the data layer is constructed using structured data and unstructured data extraction techniques,and the knowledge is stored and applied using the Neo4j graph database.Finally,rapid tracing of a pollution event in the Mulanxi River Basin is achieved using this knowledge graph.The experiment shows that the construction of this river pollution knowledge graph solves the problems of scattered data and weak correlation in water pollution events effectively,which can provide certain application value for rapid tracing of water pollution events.