Paper/Context Aware Systems:A Survey

Gandodhar, Pooja (August 21, 2021). "Context Aware Systems:A Survey". 

Abstract

The term context has been studied in different areas of Computer Science. Context-aware systems have high demand in areas like Intelligent Environments, Pervasive & Ubiquitous Computing and Ambient Intelligence. Such systems gather data and adapting system behavior accordingly using context information like physical context, computational context, and user context/tasks. Developing such context-aware applications is inherently complex and hence should be supported by adequate context information modeling and reasoning techniques. In this paper the concept of context awareness is discussed along with requirements for context identification and formulation, the procedure for converting context modeling to intelligent actions and context recognition techniques & algorithms are discussed. The applications of context aware are reviewed.

Note

• Question:
  • What is the difference between context argument in Logic Model with "context" in "context awareness intelligent system" ?
  • Purpose: Locate context argument

• Context Definition :
  • Context is any information that can be used to characterize the situation of an entity
  • A system is context-aware if it uses context to provide relevant information and/or services to the user, where relevancy depends on the user’s task
  • Gartner Glossary: Context-aware computing is a style of computing in which situational and environmental information about people, places and things is used to anticipate immediate needs and proactively offer enriched, situation-aware and usable content, functions and experiences. [1]

The following set of steps enlists procedure for converting contextual information into intelligent actions.

1. Create computational models for context acquisition with respect to tasks
2. Generalization of contextual characteristics based on the tasks
3. Aggregation of gathered information to generate an abstraction of context
4. Make choice of the algorithm or a set of algorithms to use.
5. Perform context recognition and derive inferences
6. Derive conclusions and assist the user with most suitable decision accordingly

Context Modeling Schemes

1. Key-value
2. Mark-up scheme
3. Graphical
4. Object based
5. Logic based
6. Ontology based

Further question

• How to sense more complex context? -> How to sense more complex data? -> The scheme decides how complex the data is, and how much cost it takes.

Paper/Knowledge Organization and Representation under the AI Lens

• As we comprehend context as the argument to limit the decision space, can it be grounded to some computer science theory about search space reduction?
  • How does the context reduce search space?