On the decidability of query containment under constraints
PODS '98 Proceedings of the seventeenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Querying the Semantic Web: A Formal Approach
ISWC '02 Proceedings of the First International Semantic Web Conference on The Semantic Web
Automatic categorization of query results
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
The Description Logic Handbook
The Description Logic Handbook
An algorithm based on counterfactuals for concept learning in the Semantic Web
Applied Intelligence
Grouping and Aggregate queries Over Semantic Web Databases
ICSC '07 Proceedings of the International Conference on Semantic Computing
DL-FOIL Concept Learning in Description Logics
ILP '08 Proceedings of the 18th international conference on Inductive Logic Programming
Aggregate queries over ontologies
Proceedings of the 2nd international workshop on Ontologies and information systems for the semantic web
Conjunctive query answering for the description logic SHIQ
Journal of Artificial Intelligence Research
DL-Learner: Learning Concepts in Description Logics
The Journal of Machine Learning Research
Categorize by: deductive aggregation of semantic web query results
ESWC'10 Proceedings of the 7th international conference on The Semantic Web: research and Applications - Volume Part I
ASPARAGUS - a system for automatic SPARQL query results aggregation using semantics
ICCCI'11 Proceedings of the Third international conference on Computational collective intelligence: technologies and applications - Volume Part I
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The methods proposed for aggregating results of structured queries are typically grounded on syntactic approaches. This may be inconvenient for an exploratory data retrieval, with often overwhelming number of the returned answers, requiring their further analysis and categorization. For example, if the values instantiating a grouping criterion are all different, a separate group for each answer would be created, providing no added value. In our recent work, we proposed a new approach, coined semantic grouping, where the results of conjunctive queries were grouped based on the semantics of knowledge bases (ontologies) of reference. Specifically, a user defined grouping criterion was expressed as a concept from a given ontology, and results grouped based on the concept subsumption hierarchy. In this work, we propose a novel method for the task of semantic grouping, that is based on an application of a concept refinement operator. This novel method is able to deal with some cases not handled by the initially proposed one, where, for example, a grouping criterion is a primitive concept thus not allowing for further semantic grouping of the results. In such a way, we achieve a solution able to deal with both problems: of too large and of too small number of groups.