Modeling Context Information in Pervasive Computing Systems
By Karen Henricksen, Jadwiga Indulska, Andry Rakotonirainy. International Conference on Pervasive Computing, 2002
788 citations recorded by the source corpus.
Subfields: Computer Networks and Communications, Computer Vision and Pattern Recognition
View Paper: https://www.semanticscholar.org/paper/f14e8ce6207d1cc005fc257014350400c923a47c
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Networks and Communications
- Jakob Eyvind Bardram
- Jadwiga Indulska
- Karen Henricksen
- Daqing Zhang
- Tao Gu
- Carlo Curino
- Parisa Rashidi
- Hung Keng Pung
In Computer Vision and Pattern Recognition
- Jakob Eyvind Bardram
- Jadwiga Indulska
- Karen Henricksen
- Daqing Zhang
- Tao Gu
- Parisa Rashidi
- Hung Keng Pung
- Alex Mihailidis
Citations in the corpus
- Ontology based context modeling and reasoning using OWL (2004, methodology): “[3] model context using both ER and UML models; context can be easily managed with relational databases.”
- Applications of context-aware computing in hospital work: examples and design principles (2004, neutral): “[10, 14, 12, 13, 1]).”
- The Java Context Awareness Framework (JCAF) - A Service Infrastructure and Programming Framework for Context-Aware Applications (2005, background): “Requirements for context-awareness systems and/or frameworks have been widely discussed and described [11, 17, 15, 14, 16, 1, 8, 3].”
- A Context Modeling Survey (2004, neutral): “, which is a context extension to the Object-Role Modeling (ORM) approach [22] according some contextual classification and description properties [25].”
- Developing context-aware pervasive computing applications: Models and approach (2006, methodology): “These four classes of information each display distinctive characteristics [10]; for example, sensed context is usually highly dynamic and prone to noise and sensing errors, while user-supplied information is initially reliable, but easily becomes out of date.”
- A software engineering framework for context-aware pervasive computing (2004, background): “These four classes of information each display their own distinctive characteristics [16]; for example, sensed context is usually highly dynamic and prone to noise and sensing errors, while user-supplied information is initially very reliable, but is often allowed by users to become out of date.”
- A Survey on Ambient-Assisted Living Tools for Older Adults (2013, background): “value based models [98], markup-based models [99], situation modeling languages [100], [101], and uncertain context models based on metadata information such as freshness, confidence,”
- A data-oriented survey of context models (2007, background): “The model is theoretically described in [28], and the authors introduce some possible extensions for their proposal, which is general, but at the moment can be classified into the C and E categories.”