context model (or context modeling) defines how context data are structured and maintained (It plays a key role in supporting efficient context management). It aims to produce a formal or semi-formal description of the context information that is present in a context-aware system. In other words, the context is the surrounding element for the system, and a model provides the mathematical interface and a behavioral description of the surrounding environment.
A key role of context model is to simplify and introduce greater structure into the task of developing context-aware applications.
Examples of Context Models
The Unified Modeling Language as used in systems engineering defines a context model as the physical scope of the system being designed, which could include the user as well as the environment and other actors. A System context diagram represents the context graphically..
Several examples of context models occur under other domains.
- In the situation of parsing a grammar, a context model defines the surrounding text of a lexical element. This enables a context sensitive grammar that can have deterministic or stochastic rules. In the latter case, a hidden Markov model can provide the probabilities for the surrounding context.
- A context model can also apply to the surrounding elements in a gene sequence. Like the context rules of a grammar disambiguating a lexical element, this helps to disambiguate the role of the gene.
- Within an ontology, a context model provides disambiguation of a subject via semantic analysis of information related to the subject.
- In terms of a physical environment, a context model defines the external interfaces that a system will interact with. This type of context model has been used to create models for virtual environments such as the Adaptive Vehicle Make program. A context model used during design defines land, aquatic, or atmospheric characteristics (stated in terms of mathematical algorithms or a simulation) that the eventual product will face in the real environment.
- Nicolas Guelfi; Anthony Savidis (2006). Rapid integration of software engineering techniques. Springer. p. 131. ISBN 3-540-34063-7.
- Abdelsalam Helal; Mounir Mokhtari; Bessam Abdulrazak (2008). The Engineering Handbook of Smart Technology for Aging, Disability and Independence. Wiley. p. 592. ISBN 978-0-471-71155-1.
- Klein, Dan, and Christopher D. Manning. "A generative constituent-context model for improved grammar induction." In Proceedings of the 40th Annual Meeting on Association for Computational Linguistics, pp. 128-135. Association for Computational Linguistics, 2002.
- Delcher, Arthur L., Douglas Harmon, Simon Kasif, Owen White, and Steven L. Salzberg. "Improved microbial gene identification with GLIMMER." Nucleic acids research 27, no. 23 (1999): 4636-4641.
- Wang, Xiao Hang; Zhang, D. Qing; Gu, Tao; Pung, Hung Keng (2004). "Ontology based context modeling and reasoning using OWL". Proceedings of the Second IEEE Annual Conference on Pervasive Computing and Communications Workshops. IEEE: 18–22. CiteSeerX: 10
.1 .1 .3 .9626.
- Gu, Tao; Wang, Xiao Hang; Pung, Hung Keng; Zhang, Da Qing (2004). "An ontology-based context model in intelligent environments" (PDF). Proceedings of communication networks and distributed systems modeling and simulation conference. 2004: 270–275.
- Component, Context, and Manufacturing Model Library – 2 (C2M2L-2), Broad Agency Announcement, DARPA-BAA-12-30, February 24, 2012