Modelling an individual’s Web search interests by utilizing navigational data

Abstract

An approach to model and quantify a userpsilas Web search interests using the userpsilas navigational data is presented. The approach is based on the premise that frequently visiting certain types of content indicates that the user is interested in that content. The proposed approach can be divided into three steps: monitoring the userpsilas navigational data; using the cumulative weight to determine a Web pagepsilas content; and employing the Naive Bayes Model for updating the userpsilas interest model. In order to demonstrate the effectiveness of the proposed model, experimental software is developed to analyze a userpsilas interests in sports. The experimental results demonstrate that the approach can effectively model the userpsilas interest. The proposed model could be integrated with personalized Web services.