A novel knowledge graph based question answering system of distribution network equipment information

Application of knowledge graph in distribution network equipment information (DNEI) management can effectively make the equipment data fusion and form a novel knowledge-oriented maintenance and management model, which has great advantages in terms of semantic retrieval capability and handling complex big data relationships. A Question-Answering System (QAS) is an advanced form of information retrieval computer program, whose development is based on the requirements for fast and accurate access to information. This system can fully understand users’ intentions and answer the questions described by the users in natural language accurately. Thus, this paper proposes a novel knowledge graph based QAS for distribution network equipment information management. Firstly, the QAS processes multi-source heterogeneous data of distribution network equipment based on the Common Information Model (CIM). Secondly, based on the processed data, the ontologies of equipment and equipment containers are constructed to build a schema layer. Thirdly, QAS performs entity learning based on the model in the schema layer and reintegrates the data. Finally, this system uses a graph database to store the processed data, and the knowledge graph is constructed. The established question-answering system based on the knowledge graph can facilitate users retrieving information on distribution network equipment more efficiently and accurately.