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As for the data sparsity and cool boot problem, this paper brings forward a social network recommendation means combined with social tags and trust relations. It collects major information relating to social trust relations, item tag information and user rating matrix based on probabilistic matrix factorization. All the data resources from different dimensions are connected through shared users potential spaces (or item potential spaces). The above mentioned two types of spaces can be obtained by probabilistic matrix factorization.In this way, effective social recommendation means can be achieved. The results generated from Epinions and Movielens experiments reveal that the proposed algorithm is superior to the existing Trust-based Social Recommendation or Social Tag Recommendation especially for active users with only a few rating records. [ABSTRACT FROM AUTHOR]