REAL-TIME BROWSING ASSISTANT ON WEB

Abstract

Understanding user requirements based on their interactions with a website is becoming increasingly important.Hence, in this paper, a novel real-time navigation-support system is discussed.This system builds a personalized browsing assistant based on the current user request submitted to a web server.The process involves developing a behavior model using a Discrete Time Markov Chain (DTMCs) inference process.This is then used to monitor user activities, and thereafter suggest "where to go next".Finally, it updates the model in real time using a Markovian Decision Process (MDP).To evaluate the system, we provide a user study, case studies and conduct experiments on two datasets to verify the effectiveness of our proposed system.