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Integrating the Two Main Inference Modes of NKRL, Transformations and Hypotheses

  • Gian Piero Zarri
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3730)

Abstract

An application of NKRL (Narrative Knowledge Representation Language) techniques on terrorism documents supplied by the Greek Ministry of Defence (MoD) has been carried out in the context of the IST Parmenides project; this application has required implementing the integration between the two main inferencing modes of NKRL, ‘hypotheses’ and ‘transformations’. ‘Hypothesis rules’ allow retrieving automatically from an NKRL knowledge base the information that can supply a context or a causal explanation for some known event. ‘Transformation rules’ facilitate the recovery of information from the base by ‘adapting’ (transforming) query/queries that failed to the real contents of this base. Integrating the two classes of rules means using the transformations to automatically modify the pre-defined reasoning steps of a hypothesis to build up more flexible and complete ’explanation’ scenarios.

Keywords

Transformation Rule Search Pattern Condition Schema Armed Group Conceptual Graph 
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 2005

Authors and Affiliations

  • Gian Piero Zarri
    • 1
  1. 1.LaLICC, Université Paris4-Sorbonne, Maison de la rechercheParisFrance

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