Link prediction of multimedia social network via unsupervised face recognition

We propose a new challenge for predicting links of social networks by unsupervised face recognition on photo albums. We solve the task by formulating it into Kernel Set Discovery problem. We enhance Affinity Propagation algorithm to tackle the problem with more constraints. More specifically, the face cannot appear more than once in the same photo and we impose constraints such that detected face images in the same photograph are never clustered into the same person. We construct a synthetic dataset based on AT\&T image benchmark for empirical validation. Moreover, we validate our algorithms by a real world application which contains a real friend relation on the Web 2.0 social network system. Results indicate our Constraint Affinity Propagation method is suitable to unsupervisedly predict links of social network.