This paper describes an approach to using agent technology to extend the automated discovery mechanism of the Knowledge Encapsulation Framework (KEF). KEF is a suite of tools to enable the linking of knowledge inputs (relevant, domain-specific evidence) to modeling and simulation projects, as well as other domains that require an effective collaborative workspace for knowledge-based tasks. This framework can be used to capture evidence (e.g., trusted material such as journal articles and government reports), discover new evidence (covering both trusted and social media), enable discussions surrounding domain-specific topics and provide automatically generated semantic annotations for improved corpus investigation. The current KEF implementation is presented within a semantic wiki environment, providing a simple but powerful collaborative space for team members to review, annotate, discuss and align evidence with their modeling frameworks. The novelty in this approach lies in the combination of automatically tagged and user-vetted resources, which increases user trust in the environment, leading to ease of adoption for the collaborative environment.
Revised: November 10, 2009 |
Published: September 15, 2009
Citation
Haack J.N., A.J. Cowell, E.J. Marshall, A.K. Fligg, M.L. Gregory, and L.R. McGrath. 2009.Agent-Based Knowledge Discovery for Modeling and Simulation. In 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, September 15-18, 2009, Milan, Italy, 3, 543-546. Los Alamitos, California:IEEE Computer Society Press.PNNL-SA-66191.