Abstract
This paper discusses the uses of context in knowledge representation
and reasoning (KRR). We propose to partition the theories of context
brought forward in KRR into two main classes, which we call divide-and-conquer
and compose-and-conquer. We argue that this partition provides a
possible explanation of why in KRR context is used to solve different
types of problems, or to address the same problems from very different
perspectives. The problems we use to illustrate this point are the
problem of generality, the formalization of propositional attitudes,
and knowledge and data integration.
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