A framework for organizing the space of decision problems with application to solving subjective, context-dependent problems
Developing Decision Support Systems (DSS) is a difficult task, prone to errors and susceptible to colossal failures. In order to alleviate this difficulty and its consequences, we propose a framework for organizing the space of decision problems based on problem characteristics. This organization classifies decision problems into classes that exhibit intra-class similarity. We show how classifying a new decision problem into one of the existing classes provides assistance in designing the DSS for the new problem. The classification could be based simply on problem characteristics or on the structure of the problemsolution relationships. We further show that a DSS whose goal is to support the development of DSS can be developed with the assistance of related DSS. The framework we propose could best serve researchers and practitioners if the reporting of DSS projects would follow the structure presented in this paper. In this way, additional data would be accumulated and would be available for refining the classification of the space of DSS. This in turn, would improve the support for building new DSS.
case-based reasoning software development influence knowledge graph decision problems characteristics clustering