The invention discloses a video clip recommendation method based on a graph convolution network. The video clip recommendation method comprises the steps of 1, constructing a scoring matrix of a userfor video clips; 2, processing the user set and the video clip set to obtain a user embedding matrix and a video clip embedding matrix; 3, constructing a bipartite graph based on content attributes according to the score matrix of the user; 4, inputting the constructed bipartite graph into a graph convolution network, and continuously updating a user embedding matrix; and 5, calculating a preference prediction value of the user for the segment by utilizing a graph convolution network, thereby recommending the segment to the user. According to the method, more accurate recommendation can be carried out on the user, especially for a user group with few historical data, so that the problem of cold start of an article is better solved.