Event specification in an active object-oriented database
SIGMOD '92 Proceedings of the 1992 ACM SIGMOD international conference on Management of data
Multistrategy Theory Revision: Induction and Abductionin INTHELEX
Machine Learning - Special issue on multistrategy learning
Mining Sequential Patterns: Generalizations and Performance Improvements
EDBT '96 Proceedings of the 5th International Conference on Extending Database Technology: Advances in Database Technology
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Composite Events for Active Databases: Semantics, Contexts and Detection
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Introducing Abduction into (Extensional) Inductive Logic Programming Systems
AI*IA '97 Proceedings of the 5th Congress of the Italian Association for Artificial Intelligence on Advances in Artificial Intelligence
Integrating Naïve Bayes and FOIL
The Journal of Machine Learning Research
Discovering Association Patterns in Large Spatio-temporal Databases
ICDMW '06 Proceedings of the Sixth IEEE International Conference on Data Mining - Workshops
ILP-based concept discovery in multi-relational data mining
Expert Systems with Applications: An International Journal
An interval-based representation of temporal knowledge
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 1
Event Processing in Action
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In today's security systems, the use of complex rule bases for information aggregation is more and more frequent. This does not however eliminate the possibility of wrong detections that could occur when the rule base is incomplete or inadequate. In this paper, a machine learning method is proposed to adapt complex rule bases to environmental changes and to enable them to correct design errors. In our study, complex rules have several levels of structural complexity, that leads us to propose an approach to adapt the rule base by means of an Association Rule mining algorithm coupled with Inductive logic programming for rule induction.