Design of Context Aware Recommendation Engine for Cell Phone using Bayesian Network, Fuzzy Logic, and Rough Set Theory

In this paper the authors have presented design and implementation of context aware service recommendation engine for cell phone. Context aware service recommendation engine for mobile is designed to automatically adopt its behavior to changing environment. To achieve this, an important issue to be addressed is how to effectively select services for adaptation according to the user’s current context. In this paper, the authors propose an intelligent service recommendation model. They formulate the service adaptation process by using artificial intelligence techniques like Bayesian Network, fuzzy logic and rough sets based decision table. Bayesian Network to classify the incoming call (high priority call, low priority call and unknown calls), fuzzy linguistic variables and membership degrees to define the context situations, the decision rules for adopting the policies of implementing a service. Design of Context Aware Recommendation Engine for Cell Phone using Bayesian Network, Fuzzy Logic, and Rough Set Theory