ISMIS 2000: Foundations of Intelligent Systems pp 247-255 | Cite as
A Comparative Study of Noncontextual and Contextual Dependencies
Abstract
There is current interest in generalizing Bayesian networks by using dependencies which are more general than probabilistic conditional independence (CI). Contextual dependencies, such as context-specific independence (CSI), are used to decompose a subset of the joint distribution. We have introduced a more general contextual dependency than CSI, as well as a more general noncontextual dependency than CI. We developed these probabilistic dependencies based upon a new method of expressing database dependencies. By defining database dependencies using equivalence relations, the difference between the various contextual and noncontextual dependencies can be easily understood. Moreover, this new representation of dependencies provides a convenient tool to readily derive other results.
Keywords
Equivalence Relation Bayesian Network Conditional Independence Relation Scheme Contextual DependencyPreview
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