A Heuristic Approach to Handling Sequential Information in Incremental ILP

  • Stefano Ferilli
  • Floriana Esposito
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8249)


When using Horn Clause Logic as a representation formalism, the use of uninterpreted predicates cannot fully account for the complexity of some domains. In particular, in Machine Learning frameworks based on Horn Clause Logic, purely syntactic generalization cannot be applied to these kinds of predicates, requiring specific problems to be addressed and tailored strategies and techniques to be introduced. Among others, outstanding examples are those of numeric, taxonomic or sequential information. This paper deals with the case of (multidimensional) sequential information.Coverage and generalization techniques are devised and presented, and their integration in an incremental ILP system is used to run experiments showing its performance.


Heuristic Approach Inductive Logic Programming Event Association Smart Environment Sequential Relationship 
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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© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Stefano Ferilli
    • 1
    • 2
  • Floriana Esposito
    • 1
    • 2
  1. 1.Dipartimento di InformaticaUniversità di BariItaly
  2. 2.Centro Interdipartimentale per la Logica e sue ApplicazioniUniversità di BariItaly

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