OPTIMIZING MEDIA REQUESTS WITH ENSEMBLE LEARNING

    公开(公告)号:US20240212001A1

    公开(公告)日:2024-06-27

    申请号:US18393379

    申请日:2023-12-21

    申请人: Zeta Global Corp.

    IPC分类号: G06Q30/0273

    CPC分类号: G06Q30/0275

    摘要: The subject technology optimizes media requests to improve the efficiency and reduce the costs of online media campaigns. The request optimization system may implement one or more ensemble learning techniques that leverage multiple machine learning systems trained on different datasets. The request optimization system may use the ensemble learning techniques to generate optimized media requests that account for one or more campaign goals and minimize price inefficiencies incurred while purchasing placements in online media exchanges. In various embodiments, dynamic data including real time exchange and impression data may be collected and used to retrain one or more machine learning systems. Retaining the machine learning systems on dynamic data may improve the performance of optimized media requests determined by the retrained systems.