公开(公告)号：US12047623B1

公开(公告)日：2024-07-23

申请号：US18066228

申请日：2022-12-14

Applicant: Amazon Technologies, Inc.

Inventor： Xing Zhao ,  Xuefei Wang ,  Kirtan Modi

IPC: H04N21/25 ,  H04N21/258

CPC classification number: H04N21/251 ,  H04N21/25891

Abstract: Techniques for performing a cross-platform media content personalization are described. According to some examples, a computer-implemented method includes receiving an indication, at a content delivery service from a support service for streaming media player devices, that indicates a set of one or more users of the support service that have a threshold similarity of a record of interactive activity with the support service to a record of interactive activity of a target user with the support service; determining, by the content delivery service, a subset of the users, from the set of one or more users of the support service, that have a record of interactive activity with the content delivery service; determining, by a content recommendation service of the content delivery service, a media file to provide to the target user based on the record of interactive activity with the content delivery service of the subset of the users; and presenting, by a streaming media player device of the target user and that is supported by the support service, the media file to the target user.

公开(公告)号：US11847670B1

公开(公告)日：2023-12-19

申请号：US17955783

申请日：2022-09-29

Applicant: Amazon Technologies, Inc.

Inventor： Xinyu Zhou ,  Xing Zhao ,  Qie Hu Huang ,  Kirtan Modi ,  Jae In Cho ,  Jiahui Jeff Wang

IPC: G06Q30/02 ,  G06Q30/0251 ,  G06Q30/0241 ,  G06Q30/0273

CPC classification number: G06Q30/0255 ,  G06Q30/0275 ,  G06Q30/0277

Abstract: Systems, devices, and methods are described herein for improving inventory management. As used herein, “inventory” refers to digital space at an inventory providers webpage at which content can be delivered. The disclosed techniques utilize reinforced machine learning and an offline training process to train various models with which a content request corresponding to the inventory can be classified according to historical requests and a selection process identified for the request (e.g., a direct or an indirect selection process). If an indirect selection process is chosen, the content request may be optimized for that process utilizing additional machine learning models trained using reinforced machine learning and the offline training process. The disclosed techniques enable the inventory provider to optimize content selections according to a preferred objective. The training operations are performed offline, in a training system configured to simulate the run time environment.