The Design And Implementation Of Knowledge Graph Management System Based On Accuracy Detection

With the rapid development of the Internet industry,the scale of Internet data has exploded.They contain a lot of valuable information,and the data of the Internet is large-scale,heterogeneous and diverse,and the structure is loose.It poses challenges to people in acquiring knowledge,management knowledge,and application knowledge.The knowledge graph is based on nodes and edges to represent the relationship or attributes of things.Because of its powerful semantic processing capabilities and open organizational capabilities,it has an important role in precision search,knowledge reasoning,intelligent question answering,natural language understanding,etc.,so the knowledge graph Data storage and management is an important link in the research of knowledge graph.However,most existing knowledge graph management systems focus on storage methods and retrieval speed,and are not simple and intelligent enough in data management.In data management,providing easier visual management operations and smarter management can improve the user experience.First of all,this paper proposes a classification method to detect the accuracy of knowledge graph data.The inference model is constructed by the Tran D algorithm,and then the classification function is implemented based on the link prediction and voting mechanism of inference in the knowledge graph.This classification method is used to achieve data accuracy.The purpose of testing.Experiments on the WN11 public data set show that this detection method can detect the accuracy of the data and can improve the quality of the data to a certain extent.Then,Design a more intelligent knowledge graph data management method.On the management data,the knowledge graph visualization display technology and management functions are combined to provide users with a more convenient visual management interaction method,and the above accuracy detection method is applied to the system.In the above,when users add data,the accuracy of data is judged,which improves the efficiency of data management and the quality of data..Finally,in the implementation of the system,the knowledge graph data management system is designed and implemented based on the Neo4 j graph database and My SQL database,which provides the bulk import function of knowledge graph data to facilitate data storage and realize the visual display of data.Use the Java Scriptbased D3.js plug-in library to implement visual management operations.After querying the results returned by entities or relationships,you can directly add,modify,delete,and expand related entities on the graph data in the results area.In other functions of the system,different permissions are set for each object to make management more reasonable and data safer.The system simplifies the process of data manipulation,makes management more convenient,and improves the user experience.The implementation of the management system provides users with convenient operations,improves the quality of data,and improves its functions in the future.As a data management system,it can serve precise search,knowledge question answering systems,and other intelligent applications.