Context Information Based FOREX Services

Context-aware computing is one of the key research issues in smart business applications, IoT paradigm and it is evident that it is successful in understanding the data sensed from trading environment. The success of trading depends on providing the proper personalized services to the trader based on his current context. The challenge here is to design and develop a context aware model which extracts meaningful information from raw data generated from underlying physical world. When there exists right information at right time it is possible to make effective decisions. This paper, proposes a C-IOB (Context-Information, Observation, Belief) hierarchical graphical structure model which signifies a causal relationship between low level context and high level context to reason about the customer and vendor context based beliefs. The proposed model provides accurate service with minimum computation and also reduces solution search space since the context information of a business entity is synthesized in the form of beliefs. Our research findings indicate the importance of the context based belief model in developing innovative Forex applications.