Affiliations: [a] School of Economics and Management, Hebei University of Science and Technology, Shijiazhuang, Hebei, China
| [b] School of Information and Engineering, Hebei University of Science and Technology, Shijiazhuang, Hebei, China
Correspondence:
[*]
Corresponding author. Ying Li and Pengtao Guo, E-mails: 532560881@qq.com. (Ying Li); 1003938608@qq.com. (Pengtao Guo)
Abstract: The intelligent inquiry system for metro electro-mechanical equipment faults based on the knowledge graph can effectively consolidate various semi-structured failure messages, and can provide users with quick, accurate and high-quality intelligent inquiry services such as equipment fault causes-researching and solutions-delivering, which could be really relevant to this research field and application areas. The recorded date which related to metro electromechanical equipment failures were in this research collected, consolidated and converted, so that these failures could be stored in our databases. In this context, various functions of the intelligent inquiry system have been implemented, including: natural language question analysis, language Cypher-based question and answer design, Naive Bayesian classification based on characteristic core words, and user interaction interface realization. The experimental results show that the system can effectively solve the problems related to fault handling in metro mechanical and electrical equipment, thus improving the efficiency of equipment fault maintenance.
Keywords: Intelligent inquiry, the knowledge graph, mechanical and electrical equipment fault, system construction, Neo4j
