Visual Analysis of Operational Events Based on Spatio-Temporal Evolution

By visualizing the operational data, operational situation changes of the opponent forces can be discovered in different historical periods from a series of operational incidents, and the trend of their operational activities can be predicted. Various types of operational data are obtained from open sources such as Internet and books, and stored in a designed table according to the characteristics of the data. The English dataset is interpreted to Chinese by a man-machine collaboration method and then a three-layer Bayesian probability model is used to segment the words in descriptive text. After data preprocessing, timeline scaling, statistical analysis, social network and spatial analysis technology are used in visualization of typical operational dataset. Operational dataset is visually analyzed by a spatio-temporal evolution approach, and the rules and trends of the operational activities are identified.