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Efficient Operations in Feature Terms Using Constraint Programming

  • Santiago Ontañón
  • Pedro Meseguer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7207)

Abstract

Feature Terms are a generalization of first-order terms that have been introduced in theoretical computer science in order to formalize object-oriented capabilities of declarative languages, and which have been recently receiving increased attention for their usefulness in structured machine learning applications. The main obstacle with feature terms (as well as other formal representation languages like Horn clauses or Description Logics) is that the basic operations like subsumption have a very high computational cost. In this paper we model subsumption, antiunification and unification using constraint programming (CP), solving those operations in a more efficient way than using traditional methods.

Keywords

Description Logic Constraint Programming Constraint Satisfaction Problem Inductive Logic Programming Horn Clause 
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 2012

Authors and Affiliations

  • Santiago Ontañón
    • 1
  • Pedro Meseguer
    • 1
  1. 1.IIIA-CSICArtificial Intelligence Research Institute, Spanish Scientific Research CouncilBellaterraSpain

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