Description
After more than 40 years of research in computational decision support, model selection and management is still one of the most crucial problems. With organisations facing turbulences in an environment that include constant changes in social, political, technical and economic challenges, the selection of appropriate models for decision support has become even more difficult. Most research efforts do not consider model selection itself as a major aspect of research nor do they reflect on context awareness. The paper explores the early use of Artificial Intelligence (AI) techniques to improve model selection and reviews modern Intelligent Decision Support Systems (IDSS). Since model selection is a central problem for decision makers we specifically analyse research on model selection and identify important characteristics. Based on this analysis we suggest a framework and architecture for a Context-aware Intelligent Model Selection System (CIMSS). The paper concludes with further suggestions for future research.
Recommended Citation
Wolf, Elke and Sundaram, David, "Context-aware Intelligent Model Selection System" (2017). AMCIS 2017 Proceedings. 1.
https://aisel.aisnet.org/amcis2017/SemanticsIS/Presentations/1
Context-aware Intelligent Model Selection System
After more than 40 years of research in computational decision support, model selection and management is still one of the most crucial problems. With organisations facing turbulences in an environment that include constant changes in social, political, technical and economic challenges, the selection of appropriate models for decision support has become even more difficult. Most research efforts do not consider model selection itself as a major aspect of research nor do they reflect on context awareness. The paper explores the early use of Artificial Intelligence (AI) techniques to improve model selection and reviews modern Intelligent Decision Support Systems (IDSS). Since model selection is a central problem for decision makers we specifically analyse research on model selection and identify important characteristics. Based on this analysis we suggest a framework and architecture for a Context-aware Intelligent Model Selection System (CIMSS). The paper concludes with further suggestions for future research.