标题： 在线广告中归因建模的Shapley值方法 显示英文标题

标题： Shapley Value Methods for Attribution Modeling in Online Advertising

摘要： 本文重新审视了在线广告领域归因分析中的Shapley值方法。 作为合作博弈论中的信用分配解决方案，Shapley值方法直接量化了在线广告输入在多个渠道上对广告关键绩效指标（KPI）的贡献。 我们通过开发一种替代的数学公式来简化其计算。 新公式显著提高了计算效率，从而扩展了适用范围。 基于简化的公式，我们进一步开发了有序Shapley值方法。 所提出的方法能够考虑用户访问渠道的顺序。 我们认为，通过评估用户转化旅程不同阶段的渠道归因，该方法提供了更全面的见解。 所提出的方法使用一个现实世界的在线广告活动数据集进行说明。 显示英文摘要

摘要： This paper re-examines the Shapley value methods for attribution analysis in the area of online advertising. As a credit allocation solution in cooperative game theory, Shapley value method directly quantifies the contribution of online advertising inputs to the advertising key performance indicator (KPI) across multiple channels. We simplify its calculation by developing an alternative mathematical formulation. The new formula significantly improves the computational efficiency and therefore extends the scope of applicability. Based on the simplified formula, we further develop the ordered Shapley value method. The proposed method is able to take into account the order of channels visited by users. We claim that it provides a more comprehensive insight by evaluating the attribution of channels at different stages of user conversion journeys. The proposed approaches are illustrated using a real-world online advertising campaign dataset.