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The concepts of context and context-awareness are defined and used in several approaches [12,13.14].
According to , the context is all information that can be used to characterize an entity.
Let Z = |[Z.sub.1], [Z.sub.2], ...} be a Markov chain with transition probabilities [P.sup.t.sub.i,j], where [P.sup.t.sub.i,j] is the probability that the process enters context j at time t + 1 with the condition that the process was in context i at time t.
The prior belief of an adversary (who knows a users hidden Markov chain Z and the initial probability [P.sup.0.sub.j]) about the user being in context k at time t is equal to
In this investigation, a general architecture is designed to integrate the heterogeneous sensing techniques and handle the context information for computing service provisioning toward context-aware automation and decision optimisation in the mobile applications.
Section 3 and section 4 provide a general context-aware computing architecture and the technical solutions, including context modelling method and context-aware function customisation strategy.
Context fusion is a process to obtain the high-level context by dealing with the multidomain low-level context (which consists of monitoring, sensing data, and so on) based on some methods and prior knowledge.
There is no unified standard for the classification of the context. Different researchers proposed different partition methods based on their own research backgrounds, applications, and research requirements.