公开(公告)号：US11657326B2

公开(公告)日：2023-05-23

申请号：US16994976

申请日：2020-08-17

Applicant: Oath Inc.

Inventor： Shengjun Pan ,  Tian Zhou ,  Brendan Kitts ,  Hao He ,  Bharatbhushan Shetty ,  Djordje Gligorijevic ,  Junwei Pan ,  Tingyu Mao ,  San Gultekin ,  Balaji Srinivasa Rao Paladugu ,  Jianlong Zhang ,  Sneha Thomas ,  Aaron Flores

IPC: G06Q30/00 ,  G06N20/00 ,  G06N5/04 ,  G06Q30/0273 ,  G06Q30/02

CPC classification number: G06N20/00 ,  G06N5/04 ,  G06Q30/0275

Abstract: Shaded bid values may be determined and/or submitted to one or more auction modules for participation in auctions. Auction information including at least one of impression indications associated with the auctions, sets of features associated with the auctions, the shaded bid values associated with the auctions, etc. may be stored in a database. A machine learning model may be trained using the auction information to generate a first machine learning model with feature parameters associated with features. A bid request, indicative of a second set of features, may be received. The first machine learning model may be used to determine win probabilities and/or expected bid surpluses associated with multiple shaded bid values based upon one or more feature parameters, of the feature parameters, associated with the second set of features. A shaded bid value for submission may be determined based upon the win probabilities and/or the expected bid surpluses.

公开(公告)号：US11295346B1

公开(公告)日：2022-04-05

申请号：US17028183

申请日：2020-09-22

Applicant: Oath Inc.

Inventor： Junwei Pan ,  Tian Zhou ,  Aaron Eliasib Flores

IPC: G06Q30/00 ,  G06Q30/02 ,  G06N3/08 ,  G06N20/00

Abstract: One or more computing devices, systems, and/or methods are provided. A machine learning model may be trained using a plurality of sets of information. One or more pruning operations may be performed in association with the training to generate a machine learning model with sparse vector representations associated with features of the plurality of sets of information. A request for content associated with a client device may be received. A set of features associated with the request for content may be determined. A plurality of positive signal probabilities associated with a plurality of content items may be determined using the machine learning model based upon one or more sparse vector representations, of the machine learning model, associated with the set of features. A content item may be selected from the plurality of content items for presentation via the client device based upon the plurality of positive signal probabilities.

公开(公告)号：US20220092644A1

公开(公告)日：2022-03-24

申请号：US17028162

申请日：2020-09-22

Applicant: Oath Inc.

Inventor： Junwei Pan ,  Tian Zhou ,  Aaron Eliasib Flores

IPC: G06Q30/02 ,  G06N3/08 ,  G06N7/00

Abstract: One or more computing devices, systems, and/or methods are provided. A machine learning model may be trained using a plurality of sets of information. One or more pruning operations may be performed in association with the training to generate a machine learning model with a sparse set of field weights associated with feature fields associated with features of the plurality of sets of auction information. A request for content associated with a client device may be received. A set of features associated with the request for content may be determined. Positive signal probabilities associated with a plurality of content items may be determined using the machine learning model based upon field weights, of the machine learning model, associated with the set of features. A content item may be selected from the plurality of content items for presentation via the client device based upon the positive signal probabilities.

公开(公告)号：US11651284B2

公开(公告)日：2023-05-16

申请号：US16994930

申请日：2020-08-17

Applicant: Oath Inc.

Inventor： Tian Zhou ,  Djordje Gligorijevic ,  Bharatbhushan Shetty ,  Junwei Pan ,  Brendan Kitts ,  Shengjun Pan ,  Balaji Srinivasa Rao Paladugu ,  Sneha Thomas ,  Aaron Flores

IPC: G06Q30/00 ,  G06N20/00 ,  G06F17/18 ,  G06N5/04 ,  G06Q30/02 ,  G06Q30/0273

CPC classification number: G06N20/00 ,  G06F17/18 ,  G06N5/04 ,  G06Q30/0275

Abstract: One or more computing devices, systems, and/or methods are provided. Shaded bid values may be determined and/or submitted to one or more auction modules for participation in auctions. Auction information including at least one of minimum bid values to win associated with the auctions, sets of features associated with the auctions, the shaded bid values associated with the auctions, unshaded bid values associated with the auctions, etc. may be stored in a database. A machine learning model may be trained using a loss function and/or the auction information to generate a first machine learning model with feature parameters associated with features. A bid request, indicative of a second set of features, may be received. The first machine learning model may be used to determine a shaded bid value for submission based upon one or more first feature parameters, of the feature parameters, associated with the second set of features.

公开(公告)号：US11341541B2

公开(公告)日：2022-05-24

申请号：US17028162

申请日：2020-09-22

Applicant: Oath Inc.

Inventor： Junwei Pan ,  Tian Zhou ,  Aaron Eliasib Flores

IPC: G06Q30/02 ,  G06N7/00 ,  G06N3/08 ,  G06F16/903

Abstract: One or more computing devices, systems, and/or methods are provided. A machine learning model may be trained using a plurality of sets of information. One or more pruning operations may be performed in association with the training to generate a machine learning model with a sparse set of field weights associated with feature fields associated with features of the plurality of sets of auction information. A request for content associated with a client device may be received. A set of features associated with the request for content may be determined. Positive signal probabilities associated with a plurality of content items may be determined using the machine learning model based upon field weights, of the machine learning model, associated with the set of features. A content item may be selected from the plurality of content items for presentation via the client device based upon the positive signal probabilities.

公开(公告)号：US20220092645A1

公开(公告)日：2022-03-24

申请号：US17028183

申请日：2020-09-22

Applicant: Oath Inc.

Inventor： Junwei Pan ,  Tian Zhou ,  Aaron Eliasib Flores

IPC: G06Q30/02 ,  G06N20/00 ,  G06N3/08

Abstract: One or more computing devices, systems, and/or methods are provided. A machine learning model may be trained using a plurality of sets of information. One or more pruning operations may be performed in association with the training to generate a machine learning model with sparse vector representations associated with features of the plurality of sets of information. A request for content associated with a client device may be received. A set of features associated with the request for content may be determined. A plurality of positive signal probabilities associated with a plurality of content items may be determined using the machine learning model based upon one or more sparse vector representations, of the machine learning model, associated with the set of features. A content item may be selected from the plurality of content items for presentation via the client device based upon the plurality of positive signal probabilities.