System-Level Use of Contextual Information

A system that exploits information—e.g. to support decision making— can use contextual information both in providing expectations and in resolving uncertain inferences. In the latter case, contextual reasoning involves inferring desired information (values of “problem variables”) on the basis of other available information (“context variables”). Relevant contexts are often not self-evident, but must be discovered or selected as a means to problem-solving. Therefore, context exploitation involves (a) predicting the value of contextual information to meet information needs; (b) selecting information types and sources expected to provide information useful in meeting those needs; (c) determining the relevance and quality of acquired information; and (d) applying selected information to a problem at hand. Fusion of contextual information can improve the quality of inferences, but involves concerns about the quality of the contextual information. The availability and quality of predictive models dictate the ways in which contextual information can be used. Many applications are benefitted by inference systems that adaptively discover and exploit context and refine such models to meet evolving information states and information needs.