The invention discloses a recommendation method and 
system based on a 
generative adversarial network and double clustering, and belongs to the technical field of computer application. The method comprises the following steps: firstly, reading the incomplete 
evaluation data set of a user-project establishing an incomplete 
evaluation data set of a project, then constructing a generative adversarialnetwork consisting of a generative network and a 
discriminant network, then predicting and filling missing evaluation values by utilizing the trained generative network, finally carrying out double clustering, and carrying out corresponding 
project group recommendation on different user groups according to sub-clusters obtained by the double clustering. According to the recommendation method and 
system, the trained generation network is used for filling the missing evaluation value, and the defects that a traditional method for filling the missing evaluation value such as the mean value (or the number of people) and linear interpolation is low in precision and large in error are overcome; And the filled complete 
evaluation data is clustered by using the double-clustering 
integration algorithm, so that the clustering result is more effective than that of a single double-clustering 
algorithm, the pertinence of a 
project group recommended to a specific 
user group is stronger, and the recommendation effect is improved.