Adaptive web personalization system using splay tree

Web personalization helps in understanding the user interests and creating customized experiences for users. However the user preferences changes dynamically over a period. In order to adapt with the changing information needs of the user, we have developed a novel web personalization system that captures the user changing interest by analyzing the timing information. We use splay tree, which is a self-adaptive data structure, for tracking the changing trends of the users. The proposed web personalization model is validated by building a simulation model, with real and synthetic dataset, and the quality of results are promising.