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KDD
2003
ACM

Knowledge-based data mining

9 years 10 months ago
Knowledge-based data mining
We describe techniques for combining two types of knowledge systems: expert and machine learning. Both the expert system and the learning system represent information by logical decision rules or trees. Unlike the classical views of knowledge-base evaluation or refinement, our view accepts the contents of the knowledge base as completely correct. The knowledge base and the results of its stored cases will provide direction for the discovery of new relationships in the form of newly induced decision rules. An expert system called SEAS was built to discover sales leads for computer products and solutions. The system interviews executives by asking questions, and based on the responses, recommends products that may improve a business' operations. Leveraging this expert system, we record the results of the interviews and the program's recommendations. The very same data stored by the expert system is used to find new predictive rules. Among the potential advantages of this appro...
Søren Damgaard, Sholom M. Weiss, Shubir Kap
Added 30 Nov 2009
Updated 30 Nov 2009
Type Conference
Year 2003
Where KDD
Authors Søren Damgaard, Sholom M. Weiss, Shubir Kapoor, Stephen J. Buckley
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