The proposed Visualization-Based Gap Analysis effort is aimed at providing an intuitive visualization and analysis techniques to provide analysts with the ability to understand what has happened within a domain, comprehend its current status and operations, and explore the impact of changes to the system. Link Discovery is seeking to automatically predict what relations arise in the future between objects. The proposed research intends to reformulate the link discovery problem to include predicting the strength of the link as well as create techniques to detect and predict special categories of future links; such links that arise that bridge two dense clusters of objects. Link prediction for domains other than social media and specialized literature domains will be explored.
Predictive analysis to determine future events in an industry environment based on current and past data represents an outcome of tremendous economic and societal impact. Through establishment of more rigorous capabilities for Visual Gap Analysis and Link Discovery, industry may be better able to understand what has happened, comprehend what is the current state, and obtain some grasp of what is likely to happen, may be greatly enhanced increasing productivity and allowing focus on problem resolution. The proposed effort is supported by the Industry Advisory Board and will engage individual center members. Graduate students will be trained through the research and results will be integrated into courses and industry seminars and short courses.
