Link prediction and attribute inference are two important tasks in social network mining.Most of the previous studies treated link prediction and attribute inference as different problems and sought for solutions separately.However

according to the theory of homophily

there are intrinsic relations between links and attributes in social network.We propose the link and attribute inference based on community (LAIC) solution which utilizes the community structure to connect link prediction and attribute inference.LAIC employs users' attribute and community structure for link prediction

and takes advantage of link information to get the attributes of communities for attribute inference of users.LAIC is not only able to predict attributes and links simultaneously

but also promotes the precision of link prediction and attribute inference mutually through iterations.Experiments on two real datasets verify the effectiveness of LAIC.