Generation And Recommendation Of Graphical Pivot Table Configuration In Intelligent Data Visualization System

In the era of Big Data,each data contains great value,but few companies realize that they can obtain economic benefits through data visualization,which is largely due to the fact that the ability of many current data visualization systems is a little weak,but also the lack of some intelligence,so that decision makers can not make timely decisions.This paper designs and implements an intelligent data visualization system,which solves the two most difficult technical problems:1)how to design a high-scalability system to generate the graph pivot table configuration;2)how to recommend valuable graphical pivot table configuration,which in turn includes the two important issues"how to see the next" and "how to see in the begining".In this paper,a new table algebra operator is proposed,which is used to generate the pivot configuration of a graph pivot table.Then,the graphic design can be generated based on the improved graphical language.Besides,this paper summarizes the explicit information and the implicit information of the graph pivot table configuration.On the question of intelligent recommendation,this paper summarizes and designs the derivation rules of different mark types based on data features.Then,three principles of data feature combination are proposed,and a heuristic algorithm is designed to solve the problem of single-field configuration.Finally,based on the priority principle of multi-field chart type priority problem,a graphical language based recommendation algorithm for graph pivot table configuration is proposed.The system designed and implemented in this paper has been used as a module in Netease Youdata,which is a business intelligence visualization platform,and it is used in a variety of Netease products for decision-making to make great contribution.