Tag correlation and user social relation based microblog recommendation

A microblog recommendation method based on tag correlation and user social relation is proposed via analyzing microblog features and the deficiencies of existing microblog recommendation algorithm. Specifically, a tag retrieval strategy is established to add tags for unlabeled users and users with few tags, and the user-tag matrix is then built and user-tag weights are then obtained. In order to solve the problem of sparsity of the matrix, the correlation between the tags is investigated to update the user-tag matrix. Considering the significance of user social relation for microblog recommendation, a user-user social relation similarity matrix is constructed and a mechanism is designed to iteratively obtain user interest. Experimental results show that the algorithm is effective for microblog recommendation.