A Learning Interface Agent for User Behavior Prediction

摘要

Predicting user behavior is an important issue in Human Computer Interaction research, having an essential role when developing intelligent user interfaces. A possible solution to deal with this challenge is to build an intelligent interface agent that learns to identify patterns in users behavior. The aim of this paper is to introduce a new agent based approach in predicting users behavior, using a probabilistic model. We propose an intelligent interface agent that uses a supervised learning technique in order to achieve the desired goal. We have used Aspect Oriented Programming in the development of the agent in order to benefit of the advantages of this paradigm. Based on a newly defined evaluation measure, we have determined the accuracy of the agent's prediction on a case study.