Research And Application Of Mobile User's Feature Analysis And Data Visualization

This paper designs a set of methods for analyzing mobile user characteristics and realizing data visualization.The method analyzes the characteristics of mobile users based on the data generated by mobile users and displays them through data visualization.It is composed of the following parts:feature extraction and analysis of mobile users,dimensionality reduction of moving user characteristic data,research of data visualization principle,establishment of data visualization software model of mobile user characteristics,and realization of data visualization graphical display.According to the actual usage of the mobile user,the user data is extracted from the static and dynamic features,and the dynamic characteristics of the mobile user are extracted by the user scene feature,so as to obtain the multidimensional characteristic data of the mobile user,To achieve the different characteristics of mobile users using different analytical methods for analysis.The FP-tree mining algorithm is used to excavate the moving user's travel dimension and discover the related information between the data.For the analysis of data visualization,the subject of the needs of mobile users to study the combination of different types of mobile data using different visual display.Aiming at the display of multidimensional feature data,a parallel visual coordinate based on user interaction is combined with a variety of graph visualization visualization display method,and the user multidimensional feature data is realized in two-dimensional visualization display,and the data based on mobile user characteristic analysis Visualization software model.The combination of the actual project,combined with today's popular D3 and Echarts data visualization graphics rendering tools to achieve an interactive visual analysis subsystem,and the final analysis of the results presented.Through the analysis of the display effect,the data analysis method of the mobile user characteristic proposed in the research object has achieved the expected effect on the hidden feature of the user.