Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Information Sciences: an International Journal
An Extended Relational Data Model For Probabilistic Reasoning
Journal of Intelligent Information Systems
PODS '84 Proceedings of the 3rd ACM SIGACT-SIGMOD symposium on Principles of database systems
Constructing the Dependency Structure of a Multiagent Probabilistic Network
IEEE Transactions on Knowledge and Data Engineering
A Comparative Study of Noncontextual and Contextual Dependencies
ISMIS '00 Proceedings of the 12th International Symposium on Foundations of Intelligent Systems
Contextual weak independence in Bayesian networks
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Object-oriented Bayesian networks
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
On the implication problem for probabilistic conditional independency
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
On Inferences ofWeak Multivalued Dependencies
Fundamenta Informaticae
On Inferences ofWeak Multivalued Dependencies
Fundamenta Informaticae
| Hi-index | 0.00 |
Object-oriented Bayesian networks (OOBNs) facilitate the design of large Bayesian networks by allowing Bayesian networks to be nested inside of one another. Weak conditional independence has been shown to be a necessary and sufficient condition for ensuring consistency in OOBNs. Since weak conditional independence plays such an important role in OOBNs, in this paper we establish two useful results relating weak conditional independence with weak multivalued dependency in relational databases. The first result strengthens a previous result relating conditional independence and multivalued dependency. The second result takes a step towards showing that the complete axiomatization for weak multivalued dependency is also complete for full weak conditional independence.