Method and apparatus for training information prediction models, method and apparatus for predicting information, and storage medium and device thereof

A method for predicting information, comprising:

• acquiring samples corresponding to candidate information items;
• acquiring an information prediction model, wherein the information prediction model is acquired by a method for training information prediction models;
• and
• inputting the samples into the information prediction model, and determining, based on an output result of the information prediction model, a prediction result corresponding to the candidate information items;
• wherein the method for training information prediction models comprises:
• acquiring a set of training samples corresponding to a current training period, wherein training samples in the set of training samples comprise feature items, feature attribute values corresponding to the feature items, and behavior data of a user for information items, the feature items comprising at least one of features of the user and features of the information items;
• acquiring current behavior statistics data by performing statistical collection on the behavior data in the set of training samples, and acquiring a second information prediction model by updating, based on the current behavior statistics data, first behavior statistics data in a first information prediction model, wherein the first information prediction model corresponds to a previous training period;
• and
• acquiring a trained third information prediction model by training the second information prediction model based on the set of training samples.

A computer device for training information prediction models, comprising:

• a memory, a processor, and a computer program that is stored in the memory and runnable in the processor, wherein the processor, when running the computer program, is caused to perform a method comprising:
• acquiring a set of training samples corresponding to a current training period, wherein training samples in the set of training samples comprise feature items, feature attribute values corresponding to the feature items, and behavior data of a user for information items, the feature items comprising at least one of features of the user and features of the information items;
• acquiring current behavior statistics data by performing statistical collection on the behavior data in the set of training samples, and acquiring a second information prediction model by updating, based on the current behavior statistics data, first behavior statistics data in a first information prediction model, wherein the first information prediction model corresponds to a previous training period;
• and
• acquiring a trained third information prediction model by training the second information prediction model based on the set of training samples.