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公开(公告)号:US11886964B2
公开(公告)日:2024-01-30
申请号:US17322108
申请日:2021-05-17
Applicant: Adobe Inc.
Inventor: Atanu R. Sinha , Xiang Chen , Sungchul Kim , Omar Rahman , Jean Bernard Hishamunda , Goutham Srivatsav Arra , Shiv Kumar Saini
IPC: G06N20/00 , G06F3/0484 , H04L67/50
CPC classification number: G06N20/00 , G06F3/0484 , H04L67/535
Abstract: Methods and systems disclosed herein relate generally to systems and methods for using a machine-learning model to predict user-engagement levels of users in response to presentation of future interactive content. A content provider system accesses a machine-learning model, which was trained using a training dataset including previous user-device actions performed by a plurality of users in response to previous interactive content. The content provider system receives user-activity data of a particular user and applies the machine-learning model to the user-activity data, in which the user-activity data includes user-device actions performed by the particular user in response to interactive content. The machine-learning model generates an output including a categorical value that represents a predicted user-engagement level of the particular user in response to a presentation of the future interactive content.
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公开(公告)号:US20220366299A1
公开(公告)日:2022-11-17
申请号:US17322108
申请日:2021-05-17
Applicant: Adobe Inc.
Inventor: Atanu R. Sinha , Xiang Chen , Sungchul Kim , Omar Rahman , Jean Bernard Hishamunda , Goutham Srivatsav Arra
IPC: G06N20/00 , G06F3/0484 , H04L29/08
Abstract: Methods and systems disclosed herein relate generally to systems and methods for using a machine-learning model to predict user-engagement levels of users in response to presentation of future interactive content. A content provider system accesses a machine-learning model, which was trained using a training dataset including previous user-device actions performed by a plurality of users in response to previous interactive content. The content provider system receives user-activity data of a particular user and applies the machine-learning model to the user-activity data, in which the user-activity data includes user-device actions performed by the particular user in response to interactive content. The machine-learning model generates an output including a categorical value that represents a predicted user-engagement level of the particular user in response to a presentation of the future interactive content.
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