Abstract
The description logic \(\ensuremath{\mathcal{EL}^+}\) has recently proved practically useful in the life science domain with presence of several large-scale biomedical ontologies such as Snomed ct. To deal with ontologies of this scale, standard reasoning of classification is essential but not sufficient. The ability to extract relevant fragments from a large ontology and to incrementally classify it has become more crucial to support ontology design, maintenance and re-use. In this paper, we propose a pragmatic approach to module extraction and incremental classification for \(\ensuremath{\mathcal{EL}^+}\) ontologies and report on empirical evaluations of our algorithms which have been implemented as an extension of the CEL reasoner.
Supported by DFG-Project under grant BA 1122/11-1 and EU-Project TONES.
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Suntisrivaraporn, B. (2008). Module Extraction and Incremental Classification: A Pragmatic Approach for \(\ensuremath{\mathcal{EL}^+}\) Ontologies. In: Bechhofer, S., Hauswirth, M., Hoffmann, J., Koubarakis, M. (eds) The Semantic Web: Research and Applications. ESWC 2008. Lecture Notes in Computer Science, vol 5021. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-68234-9_19
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DOI: https://doi.org/10.1007/978-3-540-68234-9_19
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