Principles of database and knowledge-base systems, Vol. I
Principles of database and knowledge-base systems, Vol. I
Semantic database modeling: survey, applications, and research issues
ACM Computing Surveys (CSUR)
Journal of Logic Programming
ACM Computing Surveys (CSUR)
Sesame: A Generic Architecture for Storing and Querying RDF and RDF Schema
ISWC '02 Proceedings of the First International Semantic Web Conference on The Semantic Web
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
The description logic handbook
Ontology-based integration for relational databases
Proceedings of the 2006 ACM symposium on Applied computing
Methods in biomedical ontology
Journal of Biomedical Informatics - Special issue: Biomedical ontologies
Bridging the gap between OWL and relational databases
Proceedings of the 16th international conference on World Wide Web
Development of NeuroElectroMagnetic ontologies(NEMO): a framework for mining brainwave ontologies
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
A framework to support automated classification and labeling of brain electromagnetic patterns
Computational Intelligence and Neuroscience - Regular issue
OWL-QL-a language for deductive query answering on the Semantic Web
Web Semantics: Science, Services and Agents on the World Wide Web
LUBM: A benchmark for OWL knowledge base systems
Web Semantics: Science, Services and Agents on the World Wide Web
Detecting Inconsistencies in the Gene Ontology Using Ontology Databases with Not-gadgets
OTM '09 Proceedings of the Confederated International Conferences, CoopIS, DOA, IS, and ODBASE 2009 on On the Move to Meaningful Internet Systems: Part II
Using ontology databases for scalable query answering, inconsistency detection, and data integration
Journal of Intelligent Information Systems
PAKDD'10 Proceedings of the 14th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining - Volume Part II
Hi-index | 0.00 |
We propose an automatic method for modeling a relational database that uses SQL triggers and foreign-keys to efficiently answer positive semantic queries about ground instances for a Semantic Web ontology. In contrast with existing knowledge-based approaches, we expend additional space in the database to reduce reasoning at query time. This implementation significantly improves query response time by allowing the system to disregard integrity constraints and other kinds of inferences at run-time. The surprising result of our approach is that load-time appears unaffected, even for medium-sized ontologies. We applied our methodology to the study of brain electroencephalographic (EEG and ERP) data. This case study demonstrates how our methodology can be used to proactively drive the design, storage and exchange of knowledge based on EEG/ERP ontologies.