Construction And Application Of Urban Public Travel Knowledge Graph

With the rapid development of China’s economy and computer technology.The development of knowledge graph and its flexible application greatly promote the development of knowledge graph application.The construction of public travel knowledge map is the extension of geographic Knowledge Graph.In view of the shortcomings of predecessors in the geographic knowledge map at the construction level,this study combined geographical features,traffic entities,spatio-temporal attributes and other data to build the public travel Knowledge Graph.On the one hand,public travel knowledge map and spatial analysis are used to detect traffic congestion,on the other hand,the breadth analysis algorithm is used to query and analyze the constructed public travel knowledge map to realize the application of COVID-19 transmission risk prediction.This paper applies the knowledge map to the study of public transport travel,and researches the construction of the knowledge map of urban bus travel and its application analysis.The topic selection has important theoretical significance and practical value.The main work of this study is as follows:Based on the research results of knowledge graph theory in computer field,this paper analyzes the concept,connotation and research status of geographical knowledge graph.Traffic knowledge is used to realize the highly coupling of traffic domain ontology knowledge and operation,and to achieve the practical application of constructing traffic knowledge system.Through the analysis and mining of traffic data,the concept,category,relationship and attribute constraint of traffic data are defined.Through the analysis,the ontology model of traffic knowledge is established to promote the rapid transformation and integration of geographical knowledge,and provide support for the intelligent processing and intelligent services of geographical information.Aiming at the ontology and data features in the process of traffic knowledge representation,nodes and relationships based on road data are designed,and map database of public travel knowledge is constructed and visualized.Mr.Chen Shupeng pioneered the application of knowledge map in the field of geographical knowledge.Based on the existing results,this study combined with the characteristics of traffic entities to build public travel knowledge map,to realize the transformation of traffic data to traffic knowledge.The visualization of the map makes the traffic information more intuitive and comprehensive to provide people with useful knowledge.Based on the map of public travel knowledge combined with geographic grid,traffic congestion detection is carried out through spatial analysis.In the spatial analysis,the grid is used instead of the layer as the index unit to save the user’s waiting time.In order to better evaluate the changes of traffic congestion state caused by dynamic changes over time,grid analysis is used to disperse the changes occurring at a certain point to each area.By using breadth first algorithm,COVID-19 patient traceability is realized in the public travel knowledge map and added to the map database,providing analysis cases for the decision-making of traffic problems.By comparing with the retrieval time of relational data,it is found that the tracing process based on knowledge graph is more advantageous.