优化广告牌标签分配，提升精准投放效果
An Effective Tag Assignment Approach for Billboard Advertisement
- 提出迭代分配法，实现标签到多个广告位的高效映射
- 在真实轨迹与广告数据集上验证，影响力提升显著
- 适合城市智能广告投放与数字营销从业者参考
广告牌广告因其高投资回报率而日益流行。为提升其效果，需将产品相关信息精准传递给目标人群。这依赖于将相关标签正确匹配至广告位。我们称此为广告牌中的标签分配问题。给定轨迹数据、广告牌数据库以及选定的广告位和标签，目标是输出一个映射，使影响范围最大化。我们将该问题建模为一种变体的二分图匹配——一对一多匹配（One-To-Many Bipartite Matching, OMBM）。与传统二分图匹配不同，此处一个标签可分配至多个广告位，但一个广告位只能对应一个标签。本文提出一种迭代分配方法，逐步将标签分配至广告位。通过实例说明方法原理，并进行复杂度分析。在真实轨迹与广告牌数据集上的实验结果证明了该方法在有效性和效率上的优越性。
原文摘要 · Abstract (English)
Billboard Advertisement has gained popularity due to its significant outrage in return on investment. To make this advertisement approach more effective, the relevant information about the product needs to be reached to the relevant set of people. This can be achieved if the relevant set of tags can be mapped to the correct slots. Formally, we call this problem the Tag Assignment Problem in Billboard Advertisement. Given trajectory, billboard database, and a set of selected billboard slots and tags, this problem asks to output a mapping of selected tags to the selected slots so that the influence is maximized. We model this as a variant of traditional bipartite matching called One-To-Many Bipartite Matching (OMBM). Unlike traditional bipartite matching, a tag can be assigned to only one slot; in the OMBM, a tag can be assigned to multiple slots while the vice versa can not happen. We propose an iterative solution approach that incrementally allocates the tags to the slots. The proposed methodology has been explained with an illustrated example. A complexity analysis of the proposed solution approach has also been conducted. The experimental results on real-world trajectory and billboard datasets prove our claim on the effectiveness and efficiency of the proposed solution.
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