Knowledge base refinement and theory revision
Proceedings of the sixth international workshop on Machine learning
The role of experimentation in scientific theory revision
Proceedings of the sixth international workshop on Machine learning
Reduction rules for resolution-based systems
Artificial Intelligence
FLEX: A Tolerant and Cooperative User Interface to Databases
IEEE Transactions on Knowledge and Data Engineering
Machine Learning
Constraints for Improving the Generation of Intensional Answers in a Deductive Database
Proceedings of the Fifth International Conference on Data Engineering
An Attribute-Oriented Approach for Learning Classification Rules from Relational Databases
Proceedings of the Sixth International Conference on Data Engineering
Conceptual Models and Architectures for Advanced Information Systems
Applied Intelligence
SSDBM '96 Proceedings of the Eighth International Conference on Scientific and Statistical Database Management
Query Initiated Discovery of Interesting Association Rules
DS '98 Proceedings of the First International Conference on Discovery Science
MASSON: discovering commonalities in collection of objects using genetic programming
GECCO '96 Proceedings of the 1st annual conference on Genetic and evolutionary computation
A New Method of Causal Association Rule Mining Based on Language Field
ICIC '07 Proceedings of the 3rd International Conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence
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A concept for knowledge discovery and evolution in databases is described. The key issues include: using a database query to discover new rules; using not only positive examples (answer to a query), but also negative examples to discover new rules; and harmonizing existing rules with the new rules. A tool for characterizing the exceptions in databases and evolving knowledge as a database evolves is developed.