A Novel Social Event Recommendation Method Based on Social and Collaborative Friendships

• Main Authors: Yu-Chun Sun, 孫羽君
• Other Authors: 陳建錦
• Format: Others
• Language: en_US
• Published: 2013
• Online Access: http://ndltd.ncl.edu.tw/handle/48359139831418760073

碩士 === 國立臺灣大學 === 資訊管理學研究所 === 101 === Many social network sites (SNSs) provide social event functions to facilitate user interactions. However, it is difficult for users to find interesting events among the huge number posted on such sites. In this paper, we investigate the problem and propose a social event recommendation method that exploits user’s social and collaborative friendships to recommend events of interest. As events are one-and-only items, their ratings are not available until they are over. Hence, traditional recommendation methods are incapable of event recommendation because they need sufficient ratings to generate recommendations. Instead of using ratings, we analyze the behavior patterns of social network users to measure their social and collaborative friendships. The friendships are aggregated to identify the acquaintances of a user and events relevant to the preferences of the acquaintances and the user are recommended. The results of experiments show that the proposed method is effective and it outperforms many well-known recommendation methods.