The invention discloses a multi-relationship collaborative filtering recommendation method based on a dynamic graph attention network. The method comprises the following steps: S1, performing data acquisition and processing; S2, dividing a data set; S3, constructing a fusion model; and S4, model training and project recommendation. According to the invention, a recurrent neural network (RNN) is used for modeling behaviors of a user in a session, the current interest of the user is captured through RNN potential representation, the influence of friends related to the user is captured through agraph attention network, the influence of each friend is weighed by measuring the characteristics of movement along each side according to an attention mechanism, and the current user representation and the social friend representation are combined; the project relationship is obtained from the interaction data of the user and the project, the project relationship and the user dynamic social relationship are fused into the learning process of the user and the project interaction, the influence of multiple relationships on the user and the project interaction is learned, and the recommendationaccuracy is improved, so that the model can better model the user preference.