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Hybrid Learning System for Adaptive Complex Event Processing

  • Jean-René Coffi
  • Christophe Marsala
  • Nicolas Museux
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6943)

Abstract

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.

Keywords

Association Rule Logic Program Rule Base Frequent Itemsets Inductive Logic Programming 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Jean-René Coffi
    • 1
    • 2
  • Christophe Marsala
    • 2
  • Nicolas Museux
    • 1
  1. 1.Thales Research and TechnologyPalaiseauFrance
  2. 2.LIP6/UPMCParisFrance

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