Abstract: In social media,recommending suitable updates for users can not only reduce information searching time,but also improve users’ stickiness for social media.In order to improve the recommendation accuracy of updates in social media,this paper proposed a linear model based learning to ranking algorithm for updates.Firstly,according to attribu-tes of social media,we defined corresponding bias features,and proposed a linear model based latent bias model.Se-condly,according to features of update and recipients,we defined corresponding linear feature model.Finally,combining the latent bias model and the feature model,we proposed a linear model with temporal effect.The experiments show that,compared with related works,the proposed algorithm has better prediction accuracy and higher execution efficiency.

Key words: Social media streaming,Ranking,Learn to rank,Linear model