Information DiscovEry Assistant that Learns (IDEAL)

Information analysts are increasingly drowning in a flood of human and computer generated information. The paperless office, the World Wide Web, and advances in document management and analysis technologies are making it increasingly difficult to identify and utilize key information. Improvements in semantic modeling, natural language processing, and collaboration technology may provide significant leverage to address this problem. Knowledge Based Systems, Inc. (KBSI) proposes to establish innovative enabling methods that target the challenge of semantic information analysis to facilitate iterative and adaptive discovery of information content associated with imprecisely specified information needs. The proposed approach is expected to empower analysts working on complex knowledge discovery tasks by dynamically forming collaborative groups of individuals who are currently investigating similar issues, while requiring minimal or no direct input from each analyst with respect to the goals of their current assignment. The proposed new capability is referred to as the Information DiscovEry Assistant that Learns (IDEAL). The proposed Phase II projects will enhance and refine the IDEAL methods, enhance and refine the IDEAL architecture, and demonstrate the practical benefits of the innovation by building and demonstrating focused transition applications.