Unifying default reasoning and belief revision in a modal framework
Artificial Intelligence
Interactive theory revision: an inductive logic programming approach
Interactive theory revision: an inductive logic programming approach
Learning by discovering concept hierarchies
Artificial Intelligence
Dynamic rule refinement in knowledge-based data mining systems
Decision Support Systems - Special issue on decision support in the new millennium
Decision Support Systems and Intelligent Systems
Decision Support Systems and Intelligent Systems
Knowledge refinement based on the discovery of unexpected patterns in data mining
Decision Support Systems - Special issue: Formal modeling and electronic commerce
Mobile clinical support system for pediatric emergencies
Decision Support Systems
ACM SIGKDD Explorations Newsletter
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An automatic data-based revision method of probabilistic multi-attribute decision models is proposed. Data-based revision of decision models is defined as follows: given an existing model and a set of data items, revise the model to match the data items. We propose and experimentally evaluate a method for the revision of probability distributions in qualitative hierarchical multi-attribute models of DEX methodology. The revision method is automatic, but limited to the modification of probability distributions in utility functions. The method is experimentally evaluated in an artificial domain. In all experiments, the classification accuracy of the revised model was improved and the changes of the model correctly reflected the simulated changes in the decision environment.