1. 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

2. 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

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