Dynamic User Attribute Discovery on Social Media

摘要：

　　Social media service defines a new paradigm of people communicating,self-expressing and sharing on the Web.Users in todays social media platforms often post contents,inferring their interests/attributes,which are significant for manyWeb services such as social recommendation,personalized searching and online advertising.User attributes are temporally dynamic along with internal interest changing and external influence.Based on topic modeling,we present a probabilistic method for dynamic user attribute discovery.Our method automatically detects user attributes and models the dynamics using time windows and decay function,thereby facilitating more accurate recommendation.Evaluation on a Sina Weibo dataset shows the superiority in terms of precision,recall and F-measure as compared to baselines,such as static user attribute modeling.

关键词： Dynamic user attribute Topic model Time window

作者: Xiu Huang Yang Yang Yue Hu Fumin Shen Jie Shao

作者单位: School of Computer Science and Engineering,University of Electronic Science and Technology of China,Chengdu,China

会议类型: 国际会议

会议名称: International Asia-Pacific Web Conference(第18届国际亚太互联网大会)

会议地点: 苏州

会议语种:英文

页码: 256-267

在线出版日期: 2016-09-23（万方平台首次上网日期，不代表论文的发表时间）