A Recommendation Agent for Mobile Phone Users Using Bayesian Behavior Prediction

This paper presents a novel agent system which provides a user with useful recommendations of behavior and information based on behavior prediction. The agent understands user´s context from a GPS sensor and a mobile phone, and predicts user´s future behavior based on user´s context. And the prediction of user´s future behavior can be used to provide the user with the suggestion of performing behavior and/or the recommendation of information which are relevant to the predicted user´s behavior. Here, behavior prediction is performed by Dynamic Bayesian Network, which can handle time-series data. The experimental results showed that the proposed agent system was enough to provide convenient recommendation services to users.