Efficient Module Extraction for Large Ontologies

  • Venkata Krishna Chaitanya Turlapati
  • Sreenivasa Kumar Puligundla
Part of the Communications in Computer and Information Science book series (CCIS, volume 394)


Modularity of ontologies has gained importance due to its application in ontology reasoning, ontology reuse and other areas of ontology engineering. One technique for extracting modules is by using Atomic Decomposition (AD). This paper uses MGS-Labels (Minimal Globalising Signatures) to improve the state-of-the-art approach which uses MSS-Labels (Minimal Seed Signatures) in terms of pre-processing time and memory requirement. It also improves the module extraction-time by reducing the number of containment checks in the worst case. We further improve the algorithm by introducing the notion of MGS-Space. We propose uniqueness properties about MGS-Space that help us to build indices and extract modules using simple operations on integers.


Description Logic Principal Ideal Input Signature Atomic Decomposition Module Extraction 
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 2013

Authors and Affiliations

  • Venkata Krishna Chaitanya Turlapati
    • 1
  • Sreenivasa Kumar Puligundla
    • 1
  1. 1.Department of Computer Science & EngineeringIndian Institute of Technology MadrasChennaiIndia

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