Frontiers of Computer Science, 2015, 9(4):608–622 Combining long-term and short-term user interest for personalized hashtag recommendation Jianjun YU, Tongyu ZHU Frontiers of Computer Science, 2015, 9(4):608–622

Problems & Ideas Problems of hashtag recommendation considering the personalized and temporal aspects of user interest Hashtag textual information user behavior Time factor Ideas: Topic-STG model, and a linear combined model Topic-STG: extended STG (Session-based Temporal Graph) model that uniforms user preference with textual, user behaviors and time features into one equation. LDA (Latent Dirichlet Allocation) is selected to present the implicit meaning of the hashtag Linear model: would include hot hashtags, personal short-term interest and long-term interest hashtags

Main Contributions precision of recommendation results with two approaches comparing with the baselines Diversity of top 10 recommendation with Twitter and Sina Weibo The MAP@n and 7 days’ diversity influenced by different count of latent topics