Testing implications of data dependencies
ACM Transactions on Database Systems (TODS)
Tractable Reasoning and Efficient Query Answering in Description Logics: The DL-Lite Family
Journal of Automated Reasoning
On the Influence of Description Logics Ontologies on Conceptual Similarity
EKAW '08 Proceedings of the 16th international conference on Knowledge Engineering: Practice and Patterns
ESWC 2009 Heraklion Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications
Measuring the similarity of labeled graphs
ICCBR'03 Proceedings of the 5th international conference on Case-based reasoning: Research and Development
EKAW'06 Proceedings of the 15th international conference on Managing Knowledge in a World of Networks
Probabilistic-logical web data integration
RW'11 Proceedings of the 7th international conference on Reasoning web: semantic technologies for the web of data
Introducing the new SIM-DLA semantic similarity measurement plug-in for the Protégé ontology editor
Proceedings of the 1st ACM SIGSPATIAL International Workshop on Spatial Semantics and Ontologies
Web Semantics: Science, Services and Agents on the World Wide Web
Leveraging terminological structure for object reconciliation
ESWC'10 Proceedings of the 7th international conference on The Semantic Web: research and Applications - Volume Part II
Towards fuzzy query-relaxation for RDF
ESWC'12 Proceedings of the 9th international conference on The Semantic Web: research and applications
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Computing the similarity between data elements is a basic functionality in flexible query answering systems. In the case of complex data definitions, for instance in terms of an ontology, computing the similarity between data elements becomes a non-trivial problem. In this paper, we propose a similarity measure for data described in terms of the DL-lite ontology language. In this measure, we take implicit information contained in the definition of classes and relations into account. In contrast to many other proposals for similarity measures, our proposal does not rely on structural criteria of the definitions involved but is solely based on the logical consequences that can be drawn.