An ontology for context-aware pervasive computing environments

By Harry Chen, Timothy W. Finin, Anupam Joshi. Knowledge engineering review (Print), 2003

1,094 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Vision and Pattern Recognition, Information Systems

View Paper: https://www.semanticscholar.org/paper/743b40102facbd3740b1cc3ceded3dbf4b287309

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Anupam Joshi
2. Timothy W. Finin
3. Harry Chen
4. Filip Perich
5. Florian Rosenberg
6. Schahram Dustdar
7. Matthias Baldauf
8. Daqing Zhang

In Computer Vision and Pattern Recognition

1. Schahram Dustdar
2. Florian Rosenberg
3. Matthias Baldauf
4. Timothy W. Finin
5. Anupam Joshi
6. Harry Chen
7. Filip Perich
8. Daqing Zhang

In Information Systems

1. Schahram Dustdar
2. Florian Rosenberg
3. Matthias Baldauf
4. Harry Chen
5. Timothy W. Finin
6. Anupam Joshi
7. Filip Perich
8. Daqing Zhang

Citations in the corpus

• A service-oriented middleware for building context-aware services (2005, background): “However, both Ranganathan and Campbell (2003) and Chen and Finin (2003) did not provide a performance evaluation for the feasibility of applying ontology in pervasive computing environments and their approaches did not address various characteristics of context information such as classification…”
• Towards an Extensible Context Ontology for Ambient Intelligence (2004, methodology): “Chen et al. [4] propose a context broker architecture (CoBrA) using an ontology to describe persons , places and intentions .”
• Cross-layer optimization for energy-efficient wireless communications: a survey (2009, background): “Other approaches are based on ontologies to express context entities and inference rules [35,36].”
• Context-aware systems: A literature review and classification (2009, background): “The reasons are as follows: Providing a shared and common understanding of a domain that can be communicated across people and application systems (Chen & Finin, 2003).”
• SOUPA: standard ontology for ubiquitous and pervasive applications (2004, methodology): “While the design of COBRA-ONT focuses on modeling contexts in smart meeting rooms [ 7 ], the design of MoGATU BDI ontology focuses on modeling the belief, desire, and intention of human users and software agents [23].”
• A survey on context-aware systems (2007, methodology): “Listing 1 shows parts of an COBRA-Ont example.”
• Semantic Web in the context broker architecture (2004, methodology): “We have developed a set of ontologies called COBRAONT [3] for modeling context in an intelligent meeting room.”