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English(EN) CanniUplift: A Holistic Framework for Mitigating Seller and Incentive Cannibalization in E-commerce Uplift Modeling

CanniUplift框架解决电子商务“同类相食”问题,以提高GMV

研究人员开发了CanniUplift,这是一个新框架,旨在解决电子商务增量建模中的挑战,特别是在多卖家环境中。该框架解决了两个主要问题:卖家级别的“同类相食”,即激励措施将支出在不同店铺之间转移,而没有增加平台总收入;以及激励措施级别的“同类相食”,这给增量估算引入了噪声。CanniUplift整合了平台级别全局对齐(Platform-level Global Alignment)来管理跨店铺的替代效应,以及基于兑换的分解去噪(Redemption-based Decomposition Denoising)来减少归因噪声。CanniUplift的在线部署使增量GMV提高了4.08%,并改善了投资回报率。 AI

影响 该框架可以提高电子商务中个性化营销和激励措施分配的有效性,从而实现更高的平台增长和投资回报率。

排序理由 该集群描述了一篇介绍针对特定机器学习问题的创新框架的新研究论文。

在 arXiv cs.AI 阅读 →

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CanniUplift框架解决电子商务“同类相食”问题,以提高GMV

报道来源 [3]

  1. arXiv cs.AI TIER_1 English(EN) · Zuwang He, Shihao Shu, Yuli Qu, Hanyu Gao, Ziliang Zhang, Diwei Chen, Xiangda Yan, Buyu Gao, Tanchao Zhu, Yumeng Li, Junxiong Zhu ·

    CanniUplift: A Holistic Framework for Mitigating Seller and Incentive Cannibalization in E-commerce Uplift Modeling

    arXiv:2607.05242v1 Announce Type: cross Abstract: Personalized incentive allocation is vital for e-commerce, where uplift modeling is the standard for estimating Individual Treatment Effects (ITE). However, traditional models often fail in complex multi-seller environments with v…

  2. arXiv cs.AI TIER_1 English(EN) · Junxiong Zhu ·

    CanniUplift:一种用于缓解电子商务提升模型中卖家和激励措施的“同类相食”现象的整体框架

    Personalized incentive allocation is vital for e-commerce, where uplift modeling is the standard for estimating Individual Treatment Effects (ITE). However, traditional models often fail in complex multi-seller environments with violations of the Stable Unit Treatment Value Assum…

  3. Hugging Face Daily Papers TIER_1 English(EN) ·

    CanniUplift: A Holistic Framework for Mitigating Seller and Incentive Cannibalization in E-commerce Uplift Modeling

    Personalized incentive allocation is vital for e-commerce, where uplift modeling is the standard for estimating Individual Treatment Effects (ITE). However, traditional models often fail in complex multi-seller environments with violations of the Stable Unit Treatment Value Assum…