LDA topic model for microblog recommendation

Microblog is a browser-based platform for web user´s information sharing and communication. With the rapidly increasing of microblog population, its effective recommendation function becomes necessary. This paper proposes the recommendation by the Latent Dirichlet Allocation topic model, which combines the user interest to meet their needs. It also conducts a comparative analysis between indirect and direct recommendation algorithms. The experimental results show that the indirect recommendation is more effective for the micro-blog recommendation.