公开(公告)号：US12038986B2

公开(公告)日：2024-07-16

申请号：US17242588

申请日：2021-04-28

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Chih Yao Chang ,  Hong Zhu ,  Zhenhua Dong ,  Xiuqiang He ,  Bowen Yuan

IPC: G06Q10/10 ,  G06F16/9535 ,  G06F18/10 ,  G06F18/20 ,  G06F18/214 ,  G06N20/00 ,  G06Q10/06 ,  G06Q30/02 ,  G06Q30/0282 ,  G06Q30/06

CPC classification number: G06F16/9535 ,  G06F18/10 ,  G06F18/214 ,  G06F18/285 ,  G06N20/00 ,  G06Q30/0282

Abstract: This application provides a recommendation model training method in the artificial intelligence (AI) field. The training method includes: obtaining a first training sample; processing attribute information of a first user and information about a first recommended object based on an interpolation model, to obtain an interpolation prediction label of the first training sample; and performing training by using the attribute information of the first user and the information about the first recommended object as an input to a recommendation model and using the interpolation prediction label of the first training sample as a target output value of the recommendation model, to obtain a trained recommendation model. According to the technical solutions of this application, impact of training data bias on recommendation model training can be alleviated, and recommendation model accuracy can be improved.