Context Sensitivity in Knowledge Rich Systems
author: Marko Grobelnik,
Artificial Intelligence Laboratory, Jožef Stefan Institute
published: Feb. 25, 2007, recorded: November 2006, views: 6704
published: Feb. 25, 2007, recorded: November 2006, views: 6704
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Description
The main goal of this tutorial is to provide an extensive survey of the past and current work in the area of context related topics. This includes analysis of the past work: (1) defining the notion of “context”, (2) present logic-based formalisms for dealing with contexts, (3) present probabilistic/fuzzy approaches to model context, (4) demonstrate “modelling the context” and “reasoning with contexts” in real-life applications. In addition, the presented work we will provide a synthesis of the past work in the light of a unified categorization of context-related approaches along several dimensions which appear as relevant from theoretical and practical point of view.
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Grobelnik's work from 2006, although more than a decade old, remains relevant as it underscores the ongoing challenges in AI research. Understanding context is crucial not just for retrieving information but also for making meaningful decisions. I look forward to further developments in this field and how context sensitivity will continue to shape the future of AI.
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