A Hybrid Trajectory Clustering for Predicting User Navigation

In this paper, we present a novel technique for predicting and visualizing users' future navigations. Here, user navigation is considered as the sequence of URL's visited by the user. We have used distance-based specific trajectory clustering to partition users and integrated with Markov model for predicting users' future navigation. For testing the proposed technique, we developed a tool called PNAS (Predicting and visualizing user NAvigationS), for predicting and visualizing user future navigations. We have demonstrated the effectiveness of our solution by testing the tool on user navigation data obtained from msnbc.com, and validated the result with Cross validation and Bootstrapping techniques.