Dynamic construction of belief networks
UAI '90 Proceedings of the Sixth Annual Conference on Uncertainty in Artificial Intelligence
UAI '00 Proceedings of the 16th Conference on Uncertainty in Artificial Intelligence
SPOOK: a system for probabilistic object-oriented knowledge representation
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
A Bayesian computational model of social capital in virtual communities
Communities and technologies
Mining Data and Modelling Social Capital in Virtual Learning Communities
Proceedings of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology
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Interacting with huge conditional probability tables in Bayesian belief networks makes it difficult for experts to create and employ probabilistic models. Researchers have investigated the use of graphical interfaces and knowledge engineering techniques to support experts' interaction with complex BBNs. We propose a cased-based tool (cbCPT) especially designed to apply knowledge engineering principles to CPT navigation, elicitation, maintenance and evaluation. Using this approach experts and/or knowledge engineers can define particular scenarios to visualize and elicit their corresponding CPTs. Important cases defined by experts can be saved for further inspection and maintenance of CPTs. In addition, we report on a simple usability study in which participants walked through some particular cases.