Abstract
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.
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Turlapati, V.K.C., Puligundla, S.K. (2013). Efficient Module Extraction for Large Ontologies. In: Klinov, P., Mouromtsev, D. (eds) Knowledge Engineering and the Semantic Web. KESW 2013. Communications in Computer and Information Science, vol 394. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41360-5_13
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DOI: https://doi.org/10.1007/978-3-642-41360-5_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-41359-9
Online ISBN: 978-3-642-41360-5
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