公开(公告)号：US11706470B1

公开(公告)日：2023-07-18

申请号：US17584009

申请日：2022-01-25

Applicant: Amazon Technologies, Inc.

Inventor： Xinyu Zhou ,  Qie Hu Huang ,  Shuang Li ,  Ying Zhang ,  Yongzhen Lu ,  Vamshi Krishna Surabhi ,  Vykunth Ashok ,  Robert James Victor ,  Kirtan Modi

IPC: H04N21/262 ,  H04N21/25 ,  H04N21/81 ,  H04N21/258

CPC classification number: H04N21/252 ,  H04N21/25883 ,  H04N21/26241 ,  H04N21/812

Abstract: Devices, systems, and methods are provided for on-target rate optimization for video. A method may include receiving streaming video advertisement impression data; receiving user activity data indicative of day-parts when viewers watch content; generating, based on the streaming video advertisement impression data and the survey data, using a machine learning model, a demographic probability vector, wherein each entry of the demographic probability vector is indicative of a probability that a viewer is in a respective age range of the non-overlapping demographic groups; generating, using the machine learning model, an audience recognition model with the demographic probability vector; generating a synthetic audience model predicting future advertisement viewing behavior; generating an assignment of an advertisement bid to a respective demographic group of the non-overlapping demographic groups; and generating, based on the assignment, a list of target demographic groups of the non-overlapping demographic groups for a bid request associated with the advertisement bid.

公开(公告)号：US20230239524A1

公开(公告)日：2023-07-27

申请号：US17584009

申请日：2022-01-25

Applicant: Amazon Technologies, Inc.

Inventor： Xinyu Zhou ,  Qie Hu Huang ,  Shuang Li ,  Ying Zhang ,  Yongzhen Lu ,  Vamshi Krishna Surabhi ,  Vykunth Ashok ,  Robert James Victor ,  Kirtan Modi

IPC: H04N21/25 ,  H04N21/258 ,  H04N21/81 ,  H04N21/262

CPC classification number: H04N21/252 ,  H04N21/25883 ,  H04N21/812 ,  H04N21/26241

Abstract: Devices, systems, and methods are provided for on-target rate optimization for video. A method may include receiving streaming video advertisement impression data; receiving user activity data indicative of day-parts when viewers watch content; generating, based on the streaming video advertisement impression data and the survey data, using a machine learning model, a demographic probability vector, wherein each entry of the demographic probability vector is indicative of a probability that a viewer is in a respective age range of the non-overlapping demographic groups; generating, using the machine learning model, an audience recognition model with the demographic probability vector; generating a synthetic audience model predicting future advertisement viewing behavior; generating an assignment of an advertisement bid to a respective demographic group of the non-overlapping demographic groups; and generating, based on the assignment, a list of target demographic groups of the non-overlapping demographic groups for a bid request associated with the advertisement bid.