The description logic handbook: theory, implementation, and applications
The description logic handbook: theory, implementation, and applications
ε-connections of abstract description systems
Artificial Intelligence
Formal Properties of Modularisation
Modular Ontologies
Package-Based Description Logics
Modular Ontologies
Modular reuse of ontologies: theory and practice
Journal of Artificial Intelligence Research
Minimal module extraction from DL-lite ontologies using QBF solvers
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Incremental Classification of Description Logics Ontologies
Journal of Automated Reasoning
Safe and economic re-use of ontologies: a logic-based methodology and tool support
ESWC'08 Proceedings of the 5th European semantic web conference on The semantic web: research and applications
Module extraction and incremental classification: a pragmatic approach for ƐL+ ontologies
ESWC'08 Proceedings of the 5th European semantic web conference on The semantic web: research and applications
Topicality in logic-based ontologies
ICCS'11 Proceedings of the 19th international conference on Conceptual structures for discovering knowledge
Decomposition and modular structure of BioPortal ontologies
ISWC'11 Proceedings of the 10th international conference on The semantic web - Volume Part I
The logical difference for the lightweight description logic EL
Journal of Artificial Intelligence Research
MORe: modular combination of OWL reasoners for ontology classification
ISWC'12 Proceedings of the 11th international conference on The Semantic Web - Volume Part I
Performance heterogeneity and approximate reasoning in description logic ontologies
ISWC'12 Proceedings of the 11th international conference on The Semantic Web - Volume Part I
Model-theoretic inseparability and modularity of description logic ontologies
Artificial Intelligence
Cross-domain targeted ontology subsets for annotation: The case of SNOMED CORE and RxNorm
Journal of Biomedical Informatics
Hi-index | 0.00 |
Extracting a subset of a given ontology that captures all the ontology's knowledge about a specified set of terms is a well-understood task. This task can be based, for instance, on locality-based modules. However, a single module does not allow us to understand neither topicality, connectedness, structure, or superfluous parts of an ontology, nor agreement between actual and intended modeling. The strong logical properties of locality-based modules suggest that the family of all such modules of an ontology can support comprehension of the ontology as a whole. However, extracting that family is not feasible, since the number of locality-based modules of an ontology can be exponential w.r.t. its size. In this paper we report on a new approach that enables us to efficiently extract a polynomial representation of the family of all locality-based modules of an ontology. We also describe the fundamental algorithm to pursue this task, and report on experiments carried out and results obtained.