A recommendation model training method and a related apparatus are provided. The method includes: selecting a positive sample in a sample set, and adding the positive sample to a training set, where the sample set includes the positive sample and negative samples, each sample includes n sample features, n ≥ 1, and the sample features of each sample include a feature used to represent whether the sample is a positive sample or a negative sample; calculating sampling probabilities of the plurality of negative samples in the sample set by using a preset algorithm; selecting a negative sample from the sample set based on the sampling probability, and adding the negative sample to the training set; and performing training by using the samples in the training set, to obtain a recommendation model. The recommendation model training method is applied to model training in the artificial intelligence (AI) field, so that model performance can be improved.
RECOMMENDATION MODEL TRAINING METHOD AND RELATED APPARATUS