Personalizing web recommendations using web usage mining and web semantics with time attribute

Abstract

Web personalization is the process of customizing web pages using a user's navigation patterns and interests. With the increase in the number of websites and web pages available on the internet, directing users to the web pages in their areas of interest has become a difficult problem. Various approaches have been proposed over the years and each of them has taken the solution of creating personalized web recommendations a step farther. Yet, owing to the possibilities of additional improvement, the system proposed in this paper takes generating web recommendations one more step ahead. The proposed system uses information from web usage mining, web semantics and the time spent on web pages to improve user recommendations. © 2010 Springer-Verlag Berlin Heidelberg.