Representing Context-Sensitive Knowledge in a Network Formalism: A Preliminary Report
Automated decision making is often complicated by the complexity of the knowledge involved. Much of this complexity arises from the context sensitive variations of the underlying phenomena. We propose a framework for representing descriptive, context-sensitive knowledge. Our approach attempts to integrate categorical and uncertain knowledge in a network formalism. This paper outlines the basic representation constructs, examines their expressiveness and efficiency, and discusses the potential applications of the framework.
PDF Link: /papers/92/p166-leong.pdf
AUTHOR = "Tze-Yun Leong
TITLE = "Representing Context-Sensitive Knowledge in a Network Formalism: A Preliminary Report",
BOOKTITLE = "Proceedings of the Eighth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-92)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Mateo, CA",
YEAR = "1992",
PAGES = "166--173"