CYC: a large-scale investment in knowledge infrastructure
Communications of the ACM
IEEE Internet Computing
An ontology for context-aware pervasive computing environments
The Knowledge Engineering Review
Use of ontologies in a pervasive computing environment
The Knowledge Engineering Review
Ontology-based personalized search and browsing
Web Intelligence and Agent Systems
Semantic Space: An Infrastructure for Smart Spaces
IEEE Pervasive Computing
Consistent Modelling of Users, Devices and Sensors in a Ubiquitous Computing Environment
User Modeling and User-Adapted Interaction
ONCOR: ontology- and evidence-based context reasoner
Proceedings of the 12th international conference on Intelligent user interfaces
PersonisAD: distributed, active, scrutable model framework for context-aware services
PERVASIVE'07 Proceedings of the 5th international conference on Pervasive computing
Context obfuscation for privacy via ontological descriptions
LoCA'05 Proceedings of the First international conference on Location- and Context-Awareness
An OWL-Based Knowledge Model for Combined-Process-and-Location Aware Service
Proceedings of the Symposium on Human Interface 2009 on Human Interface and the Management of Information. Information and Interaction. Part II: Held as part of HCI International 2009
Predicting Customer Models Using Behavior-Based Features in Shops
UMAP '09 Proceedings of the 17th International Conference on User Modeling, Adaptation, and Personalization: formerly UM and AH
MICAI'10 Proceedings of the 9th Mexican international conference on Advances in artificial intelligence: Part I
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There is considerable value in personalising information about people's location. Personalised Context Ontology (PECO) is an ontology for a building, and with PECO, we can provide personalised descriptions of the relevant people. For pragmatic reasons, it is important that PECO is created semi-automatically, making flexible use of a range of sources. For reasons of user control, it is important that PECO can be used to explain the personalisation. This paper describes PECO and how it is created for reasoning about a building. We also describe its use in an application called Locator, which presents information about the people in a building. PECO enables Locator to provide personalised information in two ways: it shows people of relevance and it makes use of personalised location labels. At the same time, PECO enables the user to scrutinise the reasoning about the personalisation. We report a study with eight users in which we compare a personalised and a non-adaptive versions of Locator. This indicates that people preferred the personalised version even though they could complete the designed tasks with both systems.