Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
The mythical man-month (anniversary ed.)
The mythical man-month (anniversary ed.)
Properties of Sensitivity Analysis of Bayesian Belief Networks
Annals of Mathematics and Artificial Intelligence
Building Probabilistic Networks: 'Where Do the Numbers Come From?' Guest Editors' Introduction
IEEE Transactions on Knowledge and Data Engineering
Network Engineering for Agile Belief Network Models
IEEE Transactions on Knowledge and Data Engineering
Bayesian Artificial Intelligence
Bayesian Artificial Intelligence
A case study in knowledge discovery and elicitation in an intelligent tutoring application
UAI'01 Proceedings of the Seventeenth conference on Uncertainty in artificial intelligence
Learning Bayesian networks: a unification for discrete and Gaussian domains
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
Parameterisation and evaluation of a Bayesian network for use in an ecological risk assessment
Environmental Modelling & Software
A chain-model genetic algorithm for Bayesian network structure learning
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Using Enterprise Architecture Models and Bayesian Belief Networks for Failure Impact Analysis
Service-Oriented Computing --- ICSOC 2008 Workshops
The use of a Bayesian network for web effort estimation
ICWE'07 Proceedings of the 7th international conference on Web engineering
Building an expert-based web effort estimation model using bayesian networks
EASE'09 Proceedings of the 13th international conference on Evaluation and Assessment in Software Engineering
Predicting web development effort using a bayesian network
EASE'07 Proceedings of the 11th international conference on Evaluation and Assessment in Software Engineering
Availability of enterprise IT systems: an expert-based Bayesian framework
Software Quality Control
Proceedings of the 34th International Conference on Software Engineering
Improving software effort estimation using an expert-centred approach
HCSE'12 Proceedings of the 4th international conference on Human-Centered Software Engineering
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Most documented Bayesian network (BN) applications have been built through knowledge elicitation from domain experts (DEs) The difficulties involved have led to growing interest in machine learning of BNs from data There is a further need for combining what can be learned from the data with what can be elicited from DEs In this paper, we propose a detailed methodology for this combination, specifically for the parameters of a BN.