The invention provides a
push processing method, a related device and a medium. The
push processing method comprises the following steps: acquiring a plurality of target push basic features; inputting the plurality of target pushing basic features into a probability prediction model to obtain a first probability that the to-be-pushed content belongs to long-
tail content in which the target object is interested, and training the probability prediction model based on a total
loss function, the total
loss function is the weighted sum of the long
tail task weight of each push basic feature sample in the push basic feature sample set on the long
tail task
loss function of the push basic feature sample, if the sample content meets the object interest condition and the long tail
sample condition, determining the long tail task weight of the push basic feature sample as a first value, and if the sample content meets the object interest condition and the long tail
sample condition, determining the long tail task weight of the push basic feature sample as a second value; otherwise, the weight of the long-tail task is determined to be a second value, and the first value is larger than the second value; and pushing the to-be-pushed content to the target
object based on the first probability. According to the embodiment of the invention, the quantity and quality of the pushed long-tail content are improved. The embodiment of the invention is applied to
big data,
artificial intelligence and the like.