A Class-Based Web Recommendation by User Browsing Behavior
Abstract: Using the concept of social navigation, the web pages browsed by users are used to recommend web pages to each other. After the analysis of the history of recently viewed web pages, we can learn more about the user’s interests. In the filtering of web pages, we can set up a voting method in the target class mechanism, to recommend web pages to other users that have similar interests. The toolbar is the main interface of communication with the users. Then the user can immediately get recommended web pages on the browser. The main contribution of this paper is to improve collaborative filtering, and to provide web pages for other users with similar interesting articles. As for the system, the initial filtering would lower the time required for calculation as well as the amount that need to be saved.
Presider: Janette Yuvienco, National Taiwan University