The PROMPT suite: interactive tools for ontology merging and mapping
International Journal of Human-Computer Studies
Web ontology segmentation: analysis, classification and use
Proceedings of the 15th international conference on World Wide Web
Just the right amount: extracting modules from ontologies
Proceedings of the 16th international conference on World Wide Web
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
CEL: a polynomial-time reasoner for life science ontologies
IJCAR'06 Proceedings of the Third international joint conference on Automated Reasoning
A Modularization-Based Approach to Finding All Justifications for OWL DL Entailments
ASWC '08 Proceedings of the 3rd Asian Semantic Web Conference on The Semantic Web
Survey of modular ontology techniques and their applications in the biomedical domain
Integrated Computer-Aided Engineering - Selected papers from the IEEE Conference on Information Reuse and Integration (IRI), July 13-15, 2008
Goal-Directed Module Extraction for Explaining OWL DL Entailments
ISWC '09 Proceedings of the 8th International Semantic Web Conference
Incremental Classification of Description Logics Ontologies
Journal of Automated Reasoning
The modular structure of an ontology: an empirical study
Proceedings of the 2010 conference on Modular Ontologies: Proceedings of the Fourth International Workshop (WoMO 2010)
The modular structure of an ontology: atomic decomposition
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume Three
Model-theoretic inseparability and modularity of description logic ontologies
Artificial Intelligence
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The description logic ƐL+ 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 ƐL+ ontologies and report on empirical evaluations of our algorithms which have been implemented as an extension of the CEL reasoner.