Fusion, propagation, and structuring in belief networks
Artificial Intelligence
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in expert systems: theory and algorithms
Probabilistic reasoning in expert systems: theory and algorithms
A simplied universal relation assumption and its properties
ACM Transactions on Database Systems (TODS)
Efficient optimization of a class of relational expressions
ACM Transactions on Database Systems (TODS)
Normalization and hierarchical dependencies in the relational data model
ACM Transactions on Database Systems (TODS)
Multivalued dependencies and a new normal form for relational databases
ACM Transactions on Database Systems (TODS)
Subset Dependencies and a Completeness Result for a Subclass of Embedded Multivalued Dependencies
Journal of the ACM (JACM)
On the Desirability of Acyclic Database Schemes
Journal of the ACM (JACM)
A complete axiomatization for functional and multivalued dependencies in database relations
SIGMOD '77 Proceedings of the 1977 ACM SIGMOD international conference on Management of data
Uncertain Information Processing in Expert Systems
Uncertain Information Processing in Expert Systems
Representation of Bayesian Networks as Relational Databases
IPMU'94 Selected papers from the 5th International Conference on Processing and Management of Uncertainty in Knowledge-Based Systems, Advances in Intelligent Computing
Graphs and Hypergraphs
Theory of Relational Databases
Theory of Relational Databases
A method for implementing a probabilistic model as a relational database
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
An Extended Relational Data Model For Probabilistic Reasoning
Journal of Intelligent Information Systems
Constructing the Dependency Structure of a Multiagent Probabilistic Network
IEEE Transactions on Knowledge and Data Engineering
Equivalent Characterization of a Class of Conditional Probabilistic Independencies
RSCTC '98 Proceedings of the First International Conference on Rough Sets and Current Trends in Computing
The membership problem for probabilistic and data dependencies
Technologies for constructing intelligent systems
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Axiomatization has been widely used for testing logical implications. This paper suggests a non-axiomatic method, the chase, to test if a new dependency follows from a given set of probabilistic dependencies. Although the chase computation may require exponential time in some cases, this technique is a powerful tool for establishing nontrivial theoretical results. More importantly, this approach provides valuable insight into the intriguing connection between relational databases and probabilistic reasoning systems.