Modelling an individual’s Web search interests by utilizing navigational data
Hao Wen, Liping Fang, Ling Guan · 2008
An approach to model and quantify a user’s Web search interests using the user’s 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 user’s navigational data; using the cumulative weight to determine a Web page’s content; and employing the Naïve Bayes Model for updating the user’s interest model. In order to demonstrate the effectiveness of the proposed model, experimental software is developed to analyze a user’s interests in sports. The experimental results demonstrate that the approach can effectively model the user’s interest. The proposed model could be integrated with personalized Web services.