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Analyzing the AIR Language: A Semantic Web (Production) Rule Language

  • Ankesh Khandelwal
  • Jie Bao
  • Lalana Kagal
  • Ian Jacobi
  • Li Ding
  • James Hendler
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6333)

Abstract

The Accountability In RDF (AIR) language is an N3-based, Semantic Web production rule language that supports nested activation of rules, negation, closed world reasoning, scoped contextualized reasoning, and explanation of inferred facts. Each AIR rule has unique identifier (typically an HTTP URI) that supports reuse of rule. In this paper we analyze the semantics of AIR language by: i) giving the declarative semantics that support the reasoning algorithm, ii) providing complexity of AIR inference; and iii) evaluating the expressiveness of language by encoding Logic Programs of different expressivities in AIR.

Keywords

Logic Program Logic Programming Predicate Symbol Graph Pattern Active Rule 
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 2010

Authors and Affiliations

  • Ankesh Khandelwal
    • 1
  • Jie Bao
    • 1
  • Lalana Kagal
    • 2
  • Ian Jacobi
    • 2
  • Li Ding
    • 1
  • James Hendler
    • 1
  1. 1.Rensselaer Polytechnic InstituteTroy
  2. 2.Massachusetts Institute of TechnologyCambridge

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