\(\mathcal{F}\)lora-2: A Rule-Based Knowledge Representation and Inference Infrastructure for the Semantic Web

  • Guizhen Yang
  • Michael Kifer
  • Chang Zhao
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2888)


\(\mathcal{F}\) lora-2 is a rule-based object-oriented knowledge base system designed for a variety of automated tasks on the Semantic Web, ranging from meta-data management to information integration to intelligent agents. The \(\mathcal{F}\) lora-2 system integrates F-logic, HiLog, and Transaction Logic into a coherent knowledge representation and inference language. The result is a flexible and natural framework that combines rule-based and object-oriented paradigms. This paper discusses the principles underlying the design of the \(\mathcal{F}\) lora-2 system and describes its salient features, including meta-programming, reification, logical database updates, encapsulation, and support for dynamic modules.


Resource Description Framework Logic Programming Path Expression Very Large Data Base Transaction Logic 
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 2003

Authors and Affiliations

  • Guizhen Yang
    • 1
  • Michael Kifer
    • 2
  • Chang Zhao
    • 2
  1. 1.Department of Computer Science and EngineeringUniversity at BuffaloBuffaloUSA
  2. 2.Department of Computer ScienceStony Brook UniversityStony BrookUSA

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