Probabilistic Financial Decision Support Framework
نویسنده
چکیده
The challenge of the business decision support domain is that a large amount of diverse information can be potentially relevant to a decision, and that, frequently, the decisions have to be made in a timely manner. This presents the potential for better decision support, but poses the challenge of building a decision support system for timely decision support. These problems motivate us to investigate ways in which the decision maker can be equipped with a flexible real time decision support system to be practical in time-critical situations. For this purpose, we propose a system that uses the Object Oriented Bayesian Knowledge Base (OOBKB) design to create a decision model at the most suitable level of detail to produce an decision recommendation within a reasonable length of time. The decision models our system uses are implemented as influence diagrams. We validate our system with experiments in a simplified investment domain. The experiments show that our system produces a quality recommendation under different situations.
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