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Very Large Scale OWL Reasoning through Distributed Computation

  • Raghava Mutharaju
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7650)

Abstract

Due to recent developments in reasoning algorithms of the various OWL profiles, the classification time for an ontology has come down drastically. For all of the popular reasoners, in order to process an ontology, an implicit assumption is that the ontology should fit in primary memory. The memory requirements for a reasoner are already quite high, and considering the ever increasing size of the data to be processed and the goal of making reasoning Web scale, this assumption becomes overly restrictive. In our work, we study several distributed classification approaches for the description logic EL+ (a fragment of OWL 2 EL profile). We present the lessons learned from each approach, our current results, and plans for future work.

Keywords

Description Logic Distribute Hash Table Link Open Data Large Ontology Tableau Algorithm 
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

  • Raghava Mutharaju
    • 1
  1. 1.Kno.e.sis CenterWright State UniversityDaytonUSA

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