Incorporating Collaborative Bookmark Recommendation with Social Network Analysis

Users collect internet resources and follow other users on the social bookmark sharing websites. Based on the interest-based social network, a hybrid recommender system incorporating collaborative and content-based filtering was built to suggest bookmark resources in this study. In the collaborative filtering, the recommender system discovers collaborative users who have similar interest with the target user; in the content-based filtering, the recommender system suggests bookmark items to the target user. An experiment was conducted to demonstrate the performances of the proposed system based on the dataset collected from a famous social bookmark sharing website.