Data-based Visualization of Scenario Maps on Potential Model

Tools for chance discovery have been used in wide range of applications, e.g. marketing, product designs, earthquake prediction. These tools visualized the map of relations among events, to be used as a scenario map for aiding users´ decision in the real world. However, the network models in the basis of these existing tools, represented by KeyGraph, have been sometimes confusing due to the complex structure of the output graph. In this paper, a potential model has been introduced for easily presenting the contextual meaning underlying the links in KeyGraph. The visual outlook of the presented tool KeyBird is like the land surface of a real island with mountains and ridges, so that the users easily interprets the output and understands the deep contextual structures missing in the data. The experimental results show the successful performance of this user interface.