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：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.