Personalized Tweet Ranking based on AHP A case study of micro-blogging message ranking in T.Sina
Micro-blogs handiness is besieging users with overloaded short snippets of tweets surging into their page. How to evaluate quality of tweets with limited content and rank them to direct user attention according to users intangible preference is a new significant topic. In this paper, we study the problem of user-specific tweet evaluation and ranking. We propose a comprehensive, personalized tweet ranking mechanism (TweetRank) with a technique of AHP (Analytic Hierarchy Process) in operational research. Based on mathematics and psychology, the AHP can quantify the weight of each impact factor and model user blur preference precisely. Case study in Chinese micro-blog platform of T.sina showed that TweetRank greatly outperformed time-based ranking currently used in T.Sina, improving percentage of interesting content in Top10 to 60％ from 20％. The work can be very helpful in directing user attention and can generalize to other recommendation contexts.
tweet mciro-blog AHP ranking personalized
Yuhong Guo Li Kang Tie Shi
Dept. of Information Technology University of International Relations Beijing, China Center of Network Administrator Henan University of Technology Zhengzhou, China Chief Editor Room Corporation of Sina Beijing, China
国际会议
桂林
英文
39-44
2010-11-17（万方平台首次上网日期，不代表论文的发表时间）