电网基建工程数据挖掘及知识图谱构建技术研究

Research on the Power Grid Project Data Mining and Knowledge Graph Construction Technologies

电网基建工程设计和施工过程中产生的大量说明书、清册等非结构化和半结构化数据可以作为电网设备、资产等基础数据的重要来源,其数据价值仍未被充分挖掘。文章在数据预处理的基础上,将双向长短期记忆神经网络模型和依存关系模型用于自然语言处理,构建基于Neo4j的基建工程知识图谱。该图谱将不同类型文件中的自然语言转化为知识库中的节点和关系,实现智能检索功能。最后,通过算例验证了所提出的知识图谱能够层次化地存储工程数据中有价值的信息,为运检、调度等部门提供了新的结构化数据来源。

An amount of unstructured and semi-structured data including specification and inventory,they are generated in the design and construction of power grid infrastructure engineering can be used as an important source of basic data from power grid equipment and assets,their data values have not been fully explored.On the basis of data preprocessing,this paper applies the dependency model and Bidirectional long short-term memory to natural language processing,and constructs the infrastructure engineering knowledge map based on Neo4j.The map transforms the natural languages in different files into nodes and relationships in the knowledge base and realizes intelligent retrieval function.Finally,an example is given to verify that the proposed knowledge map can store valuable information in engineering data hierarchically and provide a new structured data source for transportation,inspection and scheduling departments.