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Context model

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A context model is used to define the enclosing environment of some system under study. 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.

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.[1]
  • 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.[2]
  • Within an ontology, a context model provides disambiguation of a subject via semantic analysis of information related to the subject.[3][4]
  • 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.[5]

References

  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.
  2. ^ 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.
  3. ^ 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. CiteSeerx10.1.1.3.9626.
  4. ^ 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.
  5. ^ Component, Context, and Manufacturing Model Library – 2 (C2M2L-2), Broad Agency Announcement, DARPA-BAA-12-30, February 24, 2012