Toward principles for the design of ontologies used for knowledge sharing
International Journal of Human-Computer Studies - Special issue: the role of formal ontology in the information technology
Ontological engineering for B2B E-commerce
Proceedings of the international conference on Formal Ontology in Information Systems - Volume 2001
The Knowledge Model of Protégé-2000: Combining Interoperability and Flexibility
EKAW '00 Proceedings of the 12th European Workshop on Knowledge Acquisition, Modeling and Management
Semantic Web in the Context Broker Architecture
PERCOM '04 Proceedings of the Second IEEE International Conference on Pervasive Computing and Communications (PerCom'04)
An Ontology for Video Event Representation
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 7 - Volume 07
A service-oriented middleware for building context-aware services
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Hybrid context modeling: A location-based scheme using ontologies
PERCOMW '06 Proceedings of the 4th annual IEEE international conference on Pervasive Computing and Communications Workshops
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EDOCW '06 Proceedings of the 10th IEEE on International Enterprise Distributed Object Computing Conference Workshops
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Pervasive and Mobile Computing
ICDMW '07 Proceedings of the Seventh IEEE International Conference on Data Mining Workshops
Ontology-based models in pervasive computing systems
The Knowledge Engineering Review
Resolving uncertainty in context integration and abstraction: context integration and abstraction
Proceedings of the 5th international conference on Pervasive services
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Pervasive and Mobile Computing
Towards Ontology-Based Formal Verification Methods for Context Aware Systems
Pervasive '09 Proceedings of the 7th International Conference on Pervasive Computing
Using situation lattices in sensor analysis
PERCOM '09 Proceedings of the 2009 IEEE International Conference on Pervasive Computing and Communications
The hidden permutation model and location-based activity recognition
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
Review: The use of pervasive sensing for behaviour profiling - a survey
Pervasive and Mobile Computing
Activity recognition: linking low-level sensors to high-level intelligence
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Supporting pervasive computing applications with active context fusion and semantic context delivery
Pervasive and Mobile Computing
Object relevance weight pattern mining for activity recognition and segmentation
Pervasive and Mobile Computing
LOC8: A Location Model and Extensible Framework for Programming with Location
IEEE Pervasive Computing
Human-behaviour study with situation lattices
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
A long-term evaluation of sensing modalities for activity recognition
UbiComp '07 Proceedings of the 9th international conference on Ubiquitous computing
A unified semantics space model
LoCA'07 Proceedings of the 3rd international conference on Location-and context-awareness
Building reliable activity models using hierarchical shrinkage and mined ontology
PERVASIVE'06 Proceedings of the 4th international conference on Pervasive Computing
Modelling context information with ORM
OTM'05 Proceedings of the 2005 OTM Confederated international conference on On the Move to Meaningful Internet Systems
Context Inference Engine (CiE): Inferring Context
International Journal of Advanced Pervasive and Ubiquitous Computing
Ontology patterns for complex activity modelling
RuleML'13 Proceedings of the 7th international conference on Theory, Practice, and Applications of Rules on the Web
Data & Knowledge Engineering
Ontology-based Activity Recognition Framework and Services
Proceedings of International Conference on Information Integration and Web-based Applications & Services
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Recognising human activities is a problem characteristic of a wider class of systems in which algorithms interpret multi-modal sensor data to extract semantically meaningful classifications. Machine learning techniques have demonstrated progress, but the lack of underlying formal semantics impedes the potential for sharing and reusing classifications across systems. We present a top-level ontology model that facilitates the capture of domain knowledge. This model serves as a conceptual backbone when designing ontologies, linking the meaning implicit in elementary information to higher-level information that is of interest to applications. In this way it provides the common semantics for information at different levels of granularity that supports the communication, reuse and sharing of ontologies between systems.