Abstract
A knowledge-intensive problem is often not solved by an individual knowledge artifact; rather the solution needs to draw upon multiple, and even heterogeneous, knowledge artifacts. The synthesis of multiple knowledge artifacts to derive a ‘comprehensive’ knowledge artifact is a non-trivial problem. We discuss the need of knowledge morphing, and propose a Semantic Web based framework \({\cal K}\)-\({\cal MORPH}\) for deriving a context-driven integration of multiple knowledge artifacts.
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Hussain, S. (2009). \({\cal K}\)-\({\cal MORPH}\): A Semantic Web Based Knowledge Representation and Context-Driven Morphing Framework. In: Gao, Y., Japkowicz, N. (eds) Advances in Artificial Intelligence. Canadian AI 2009. Lecture Notes in Computer Science(), vol 5549. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01818-3_42
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DOI: https://doi.org/10.1007/978-3-642-01818-3_42
Publisher Name: Springer, Berlin, Heidelberg
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