本論文的貢獻在於能改善Collaborative Filtering在處理效率上缺點，提供使用者對於自己感興趣的網頁類別中，其他使用者具有相同類別的網頁資訊。 In the following research, 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 medium of communication with the users. 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 interests. As for the system, the initial filtering would lower the time required for calculation as well as the amount that needs to be saved.