Mental leaps: analogy in creative thought
Mental leaps: analogy in creative thought
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Machine Learning
Analysis of Symbolic Data: Exploratory Methods for Extracting Statistical Information from Complex Data
An Efficient k-Means Clustering Algorithm: Analysis and Implementation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Measuring Similarity between Ontologies
EKAW '02 Proceedings of the 13th International Conference on Knowledge Engineering and Knowledge Management. Ontologies and the Semantic Web
Commonality-Based ABox Retrieval
Commonality-Based ABox Retrieval
A dissimilarity measure for ALC concept descriptions
Proceedings of the 2006 ACM symposium on Applied computing
The Description Logic Handbook
The Description Logic Handbook
Realizing the Hydrogen Economy through Semantic Web Technologies
IEEE Intelligent Systems
Computing least common subsumers in description logics with existential restrictions
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
Using information content to evaluate semantic similarity in a taxonomy
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Algorithm, implementation and application of the SIM-DL similarity server
GeoS'07 Proceedings of the 2nd international conference on GeoSpatial semantics
OTM'06 Proceedings of the 2006 international conference on On the Move to Meaningful Internet Systems: AWeSOMe, CAMS, COMINF, IS, KSinBIT, MIOS-CIAO, MONET - Volume Part II
A Semantic Similarity Measure for Ontology-Based Information
FQAS '09 Proceedings of the 8th International Conference on Flexible Query Answering Systems
SemioSem: A Semiotic-Based Similarity Measure
OTM '09 Proceedings of the Confederated International Workshops and Posters on On the Move to Meaningful Internet Systems: ADI, CAMS, EI2N, ISDE, IWSSA, MONET, OnToContent, ODIS, ORM, OTM Academy, SWWS, SEMELS, Beyond SAWSDL, and COMBEK 2009
AI*IA '09: Proceedings of the XIth International Conference of the Italian Association for Artificial Intelligence Reggio Emilia on Emergent Perspectives in Artificial Intelligence
Theory and Practice of Logic Programming
Similarity for Attribute-value Representations in Fuzzy Description Logics
Proceedings of the 2010 conference on Artificial Intelligence Research and Development: Proceedings of the 13th International Conference of the Catalan Association for Artificial Intelligence
Prediction of class and property assertions on OWL ontologies through evidence combination
Proceedings of the International Conference on Web Intelligence, Mining and Semantics
Leveraging terminological structure for object reconciliation
ESWC'10 Proceedings of the 7th international conference on The Semantic Web: research and Applications - Volume Part II
ICCBR'11 Proceedings of the 19th international conference on Case-Based Reasoning Research and Development
Measuring similarity in description logics using refinement operators
ICCBR'11 Proceedings of the 19th international conference on Case-Based Reasoning Research and Development
Data Mining and Knowledge Discovery
Coupling human-and machine-driven mapping of SKOS thesauri
International Journal of Metadata, Semantics and Ontologies
A framework for semantic-based similarity measures for ELH-concepts
JELIA'12 Proceedings of the 13th European conference on Logics in Artificial Intelligence
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Similarity measures play a key role in the Semantic Web perspective. Indeed, most of the ontology related operations such as ontology learning, ontology alignment, ontology ranking and ontology population are grounded on the notion of similarity. In the last few years several similarity functions have been proposed for measuring both concept similarity and ontology similarity. However, they lack of a comprehensive formal characterization that is able to explain their behavior and value added, in particular when the ontologies are formulated in description logics languages like OWL-DL. Concept similarity functions need to be able to deal with the high expressive power of the ontology representation language, and to convey the underlying semantics of the ontology to which concepts refer. We propose a semantic similarity measure for complex Description Logics concept descriptions that elicits the underlying ontology semantics. Furthermore, we theorize a set of criteria that a measure has to satisfy in order to be compliant with a semantic expected behavior.