Capturing knowledge of user preferences: ontologies in recommender systems
Proceedings of the 1st international conference on Knowledge capture
Ontological Engineering
Evolution of mobile location-based services
Communications of the ACM - Mobile computing opportunities and challenges
The Description Logic Handbook
The Description Logic Handbook
Ontology-Based Geospatial Data Query and Integration
GIScience '08 Proceedings of the 5th international conference on Geographic Information Science
Improving an RCC-Derived Geospatial Approximation by OWL Axioms
ISWC '08 Proceedings of the 7th International Conference on The Semantic Web
Building geospatial ontologies from geographical databases
GeoS'07 Proceedings of the 2nd international conference on GeoSpatial semantics
Making web users' domain models explicit by applying ontologies
ER'07 Proceedings of the 2007 conference on Advances in conceptual modeling: foundations and applications
Geospatial semantic web: architecture of ontologies
GeoS'05 Proceedings of the First international conference on GeoSpatial Semantics
Ontology-driven Development of Personalized Location Based Services
Proceedings of the 2011 conference on Databases and Information Systems VI: Selected Papers from the Ninth International Baltic Conference, DB&IS 2010
Semantically enriching VGI in support of implicit feedback analysis
W2GIS'11 Proceedings of the 10th international conference on Web and wireless geographical information systems
Creating task-specific maps with map content transformations
Proceedings of the 1st ACM SIGSPATIAL International Workshop on MapInteraction
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Advanced Location Based Service (LBS) applications have to integrate information stored in GIS, information about users' preferences (profile) as well as contextual information and information about application itself. Ontology engineering provides methods to semantically integrate several data sources. We propose an ontology-driven LBS development framework: the paper describes the architecture of ontologies and their usage for retrieval of spatially related objects relevant to the user. Our main contribution is to enable personalised ontology driven LBS by providing a novel approach for defining personalised semantic spatial relationships by means of ontologies. The approach is illustrated by an industrial case study.