Research on collaborative filtering recommendation algorithm based on social network

For users of social-based social networking services, we propose a local random walk-based friend recommendation approach by bringing together social network and tie strength. We firstly construct a weighted friend network as the basis for friend recommendation. Then, users' similarity is determined by a local random walk-based similarity measure on a weighted friend network. Experiments show that we use real social network data to evaluate the new method. The validity of the method is illustrated.