ROBIN: A novel personal recommendation model based on information propagation

• In this paper, we propose a novel personal recommendation model, called ROBIN.
• ROBIN employs Information Propagation and the EM method to implement the recommendation task.
• Experiment results show that ROBIN achieves good performance.

With the rapid development of the Internet technology, we have now entered the era of information overloading. Recommendation System technology can recommend web resources or information to people based on his/her personal preference, and has gotten a great deal of attention and development in recent years. In this paper, by combining collaborative filtering technology and information propagation principle, we proposed ROBIN, a novel recommendation model. The ROBIN model achieves a good recommendation effect by propagating the relationship information between users and resources. Based on the ROBIN model, we designed and implemented tag recommendation algorithm named ROBIN-T. For evaluating our proposed method, we have conducted tag recommendation experiments on three real datasets and the results show that the ROBIN-T algorithm achieves good performance when compared with classical approaches.