Knowledge Graph Assisted Basketball Sport News Visualization

Abstract

Visual analysis of sports event news involves sports event analysis and news visualization, which plays an im-portant role in quick generating of event news reports, enhancing the expression of event news, and assisting event analysis. A knowledge graph based visual analytics method is proposed for basketball data news generation. The interactive visualization tools are designed for basic matches and team data of basketball games, such as basketball player data, team data and spatio-temporal data, supplemented by knowledge graph, which enriches background knowledge. Besides the overview and statistical view of basic data, it also includes the visual design of knowledge map of the background data for the game and the visual view for the spatio-temporal data of the game, so that basketball fans and ordinary readers could benefit from a multi-dimensional perspective to enjoy the various aspects of the basketball game. Therefore, the visualization system can increase the richness of sports event news, and serve basketball fans and ordinary readers better. Through the evaluation by basketball fans, general readers, and professional sports journalists, most of the average scores of each visual module are above 4 points basically under a 5-point quantitative scoring system. It is proved that the knowledge graph used in basketball event visualization has both vividness and knowledge, which enhances the expressiveness of basketball event news.