公开(公告)号：US20210200774A1

公开(公告)日：2021-07-01

申请号：US16731108

申请日：2019-12-31

Applicant: Oath Inc.

Inventor： Lakshmi Narayan Bhamidipati ,  Ravi Kant ,  Yohay Kaplan ,  Alexander Shtof

IPC: G06F16/2457 ,  G06F16/248

Abstract: One or more computing devices, systems, and/or methods for selecting content items for presentation via client devices are provided. A content event associated with a content item performed by a client device may be detected. The content item may be associated with an entity. A conversion event, associated with the entity, performed by the client device may be detected. A duration of time between the content event and the conversion event may be determined. An attribution score may be determined based upon the duration of time. A plurality of attribution scores, comprising the attribution score, may be stored in an attribution data structure associated with the content item. Responsive to receiving a request for content associated with a second client device, the content item may be selected from a plurality of content items for presentation via the second client device based upon the attribution data structure.

公开(公告)号：US11556814B2

公开(公告)日：2023-01-17

申请号：US16800504

申请日：2020-02-25

Applicant: Oath Inc.

Inventor： Alexander Shtof ,  Yair Koren ,  Yohay Kaplan

IPC: G06F17/00 ,  G06F7/00 ,  G06N5/04 ,  G06N20/00 ,  G06F16/23 ,  G06F16/2457 ,  G06N5/02 ,  G06Q30/02

Abstract: One or more computing devices, systems, and/or methods for content recommendation based upon continuity and grouping information of attributes are provided herein. User interaction data specifying whether users interacted with content items, user attributes of the users, and content attributes of the content items is obtained. A data structure is populated with the user interaction data. The data structure is modified by inserting a set of sub-fields into the data structure for a user attribute. A sub-field is populated with a value representing an option of the user attribute. The set of sub-fields are an encoding of continuity information and grouping information representing options for the user attribute. The data structure is processed using machine learning functionality to generate a model. The model is utilized to generate a prediction as to whether a user will interact with a content item.

公开(公告)号：US11182390B2

公开(公告)日：2021-11-23

申请号：US16731108

申请日：2019-12-31

Applicant: Oath Inc.

Inventor： Lakshmi Narayan Bhamidipati ,  Ravi Kant ,  Yohay Kaplan ,  Alexander Shtof

IPC: G06F17/10 ,  G06F16/2457 ,  G06F16/248

Abstract: One or more computing devices, systems, and/or methods for selecting content items for presentation via client devices are provided. A content event associated with a content item performed by a client device may be detected. The content item may be associated with an entity. A conversion event, associated with the entity, performed by the client device may be detected. A duration of time between the content event and the conversion event may be determined. An attribution score may be determined based upon the duration of time. A plurality of attribution scores, comprising the attribution score, may be stored in an attribution data structure associated with the content item. Responsive to receiving a request for content associated with a second client device, the content item may be selected from a plurality of content items for presentation via the second client device based upon the attribution data structure.

公开(公告)号：US20210264297A1

公开(公告)日：2021-08-26

申请号：US16800504

申请日：2020-02-25

Applicant: Oath Inc.

Inventor： Alexander Shtof ,  Yair Koren ,  Yohay Kaplan

IPC: G06N5/04 ,  G06N20/00 ,  G06N5/02 ,  G06F16/23 ,  G06F16/2457

Abstract: One or more computing devices, systems, and/or methods for content recommendation based upon continuity and grouping information of attributes are provided herein. User interaction data specifying whether users interacted with content items, user attributes of the users, and content attributes of the content items is obtained. A data structure is populated with the user interaction data. The data structure is modified by inserting a set of sub-fields into the data structure for a user attribute. A sub-field is populated with a value representing an option of the user attribute. The set of sub-fields are an encoding of continuity information and grouping information representing options for the user attribute. The data structure is processed using machine learning functionality to generate a model. The model is utilized to generate a prediction as to whether a user will interact with a content item.