Interactive Relation Exploration And Analysis Based On Knowledge Graph: Visualization Model And System Implementation

With the boosting of internet,IoT,and cloud computing technologies,various fields are facing the problems of storing,processing and exploring huge amounts of collected data.Challenges for that include the heterogeneity,variety,dynamics of underlying data,making it cumbersome for direct analysis in varied applications.Of all fundamental techniques for data acquisition,transmission,exploration and analysis,the most demanded scheme is a reliable means of relation discovery from multi-sourced,multi-variate,and streaming datasets.As such,this thesis focuses on the relation representation and visualization based on knowledge graph,and makes three contributions:(1)we present and implement a set of data modeling method to support relation analysis,including the object,the attribute of the object,the relation between the objects and the spatial structure of the object,knowledge graph is employed as the basic data model;(2)we summarize a visualization-driven interactive model for relation analysis by referring to the What-Why-How model recently proposed in visualization community;(3)we design and implement a prototype system that includes data collection,modeling and visualization for effective relation analysis.We demonstrate the effectiveness of our scheme with a bunch of examples.