document: 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 approach are ( a ) the capability to spot new sales trends and ( b ) the substitution of less expensive probabilistic rules that use database data instead of interviews .
doc_bio_tags: O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O B I O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O O