Artificial intelligence techniques for bid optimization used for generating dynamic online content

    公开(公告)号:US12131350B2

    公开(公告)日:2024-10-29

    申请号:US17403702

    申请日:2021-08-16

    Applicant: Adobe Inc.

    CPC classification number: G06Q30/0275 G06N20/00 G06Q30/0277

    Abstract: Techniques are disclosed for real-time bidding (e.g., for dynamic online content placement) using an optimized final bid. The final bid is determined based on a predicted clearing price and an initial bid. The initial bid represents a value to a prospective content provider, and may be computed based on campaign information. The predicted clearing price is a predicted amount paid, and may be predicted using a model trained using historical winning bids data. The clearing price may be predicted using a quantile regression model, where the quantile can be selected to control bid aggressiveness. In some cases, the quantile is determined based on pacing in an overall campaign. Once the initial bid and the predicted clearing price are calculated, the final bid is computed based on the initial bid and the predicted clearing price.

    ARTIFICIAL INTELLIGENCE TECHNIQUES FOR BID OPTIMIZATION USED FOR GENERATING DYNAMIC ONLINE CONTENT

    公开(公告)号:US20210374809A1

    公开(公告)日:2021-12-02

    申请号:US17403702

    申请日:2021-08-16

    Applicant: Adobe Inc.

    Abstract: Techniques are disclosed for real-time bidding (e.g., for dynamic online content placement) using an optimized final bid. The final bid is determined based on a predicted clearing price and an initial bid. The initial bid represents a value to a prospective content provider, and may be computed based on campaign information. The predicted clearing price is a predicted amount paid, and may be predicted using a model trained using historical winning bids data. The clearing price may be predicted using a quantile regression model, where the quantile can be selected to control bid aggressiveness. In some cases, the quantile is determined based on pacing in an overall campaign. Once the initial bid and the predicted clearing price are calculated, the final bid is computed based on the initial bid and the predicted clearing price.

    Artificial intelligence techniques for bid optimization used for generating dynamic online content

    公开(公告)号:US11127050B2

    公开(公告)日:2021-09-21

    申请号:US16687082

    申请日:2019-11-18

    Applicant: Adobe Inc.

    Abstract: Techniques are disclosed for real-time bidding (e.g., for dynamic online content placement) using an optimized final bid. The final bid is determined based on a predicted clearing price and an initial bid. The initial bid represents a value to a prospective content provider, and may be computed based on campaign information. The predicted clearing price is a predicted amount paid, and may be predicted using a model trained using historical winning bids data. The clearing price may be predicted using a quantile regression model, where the quantile can be selected to control bid aggressiveness. In some cases, the quantile is determined based on pacing in an overall campaign. Once the initial bid and the predicted clearing price are calculated, the final bid is computed based on the initial bid and the predicted clearing price.

    ARTIFICIAL INTELLIGENCE TECHNIQUES FOR BID OPTIMIZATION USED FOR GENERATING DYNAMIC ONLINE CONTENT

    公开(公告)号:US20210150585A1

    公开(公告)日:2021-05-20

    申请号:US16687082

    申请日:2019-11-18

    Applicant: Adobe Inc.

    Abstract: Techniques are disclosed for real-time bidding (e.g., for dynamic online content placement) using an optimized final bid. The final bid is determined based on a predicted clearing price and an initial bid. The initial bid represents a value to a prospective content provider, and may be computed based on campaign information. The predicted clearing price is a predicted amount paid, and may be predicted using a model trained using historical winning bids data. The clearing price may be predicted using a quantile regression model, where the quantile can be selected to control bid aggressiveness. In some cases, the quantile is determined based on pacing in an overall campaign. Once the initial bid and the predicted clearing price are calculated, the final bid is computed based on the initial bid and the predicted clearing price.

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