Data-Driven Theory Refinement Using KBDistAl

IDA, pp. 331-342, 1999.

Cited by: 5|Views47
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Abstract:

Knowledge based artificial neural networks offer an attractive approach to extending or modifying incomplete knowledge bases or domain theories through a process of data-driven theory refinement. We present an efficient algorithm for data-driven knowledge discovery and theory refinement using DistAl, a novel (inter-pattern distance based,...More

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