The present application relates to the technical field of artificial intelligence, and provides an artificial intelligence-based user rating prediction method and apparatus, a terminal, and a medium. The method comprises: calculating a saturation and a correlation of each data indicator; extracting a plurality of modelling data indicators from among the plurality of data indicators according to the saturations and the correlations, and inputting into a first input layer in a preset neural network framework; grouping all nodes of a current fully connected layer according to a preset grouping rule, determining a target node in each group, and using the plurality of target nodes of the current fully connected layer to perform fully connected training on a next fully connected layer, until training of a last fully connected layer is complete; iteratively training the preset neural network framework according to a predicted rating label outputted by a last output layer of the preset neural network framework, to obtain a user rating prediction model; using the user rating prediction model to perform rating prediction on a target user. The present application can increase the efficiency of user rating prediction, and improve the accuracy of user rating prediction.
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