公开(公告)号：US20250095047A1

公开(公告)日：2025-03-20

申请号：US18968747

申请日：2024-12-04

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Qinglin JIA ,  Jieming ZHU ,  Guohao CAI ,  Ruiming TANG ,  Zhenhua DONG

IPC: G06Q30/0601

Abstract: This application discloses an item recommendation method and a related device thereof, so that a probability of tapping an item by the user can be accurately predicted, to improve overall prediction precision of a model. The method in this application includes obtaining first information, where the first information includes attribute information of a user and attribute information of an item. The method also include processing the first information by using a first model to obtain a first processing result, where the first processing result is used to determine the item recommended to the user. Furthermore, the first model is configured to perform a linear operation on the first information to obtain second information, perform a nonlinear operation on the second information to obtain third information, and obtain the first processing result based on the third information.

公开(公告)号：US20230088171A1

公开(公告)日：2023-03-23

申请号：US17989719

申请日：2022-11-18

Applicant: HUAWEI TECHNOLOGIES CO., LTD.

Inventor： Guohao CAI ,  Gang WANG ,  Zhenhua DONG ,  Xiaoguang LI ,  Xiuqiang HE ,  Hong ZHU

IPC: G06F16/9535 ,  G06F16/954

Abstract: A method and an apparatus for training a search recommendation model, and a method and an apparatus for sorting search results are provided. The training method includes: obtaining a training sample set including a sample user behavior group sequence and a masked sample user behavior group sequence; and using the training sample set as input data, and training a search recommendation model, to obtain a trained search recommendation model, where a target of the training is to obtain the object of the response operation of the sample user after the mask processing, the search recommendation model is used to predict a label of a candidate recommendation object in search results corresponding to a query field when a target user inputs the query field, and the label is used to indicate a probability that the target user performs a response operation on the candidate recommendation object.