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In this paper, we introduce an online decision model, effectively capturing the features of real-time support in online advertising. We target small and medium-sized enterprise (SME) advertisers, who lack opportunities for exposure, and consider how to provide additional support for them to acquire advertising slots. This paper investigates two settings, single slot and multiple slots. In both scenarios, our objective is to design online support algorithms that maximize the cumulative utility of SMEs across multiple rounds within the fixed support budget. Technically, we propose a dual-based online algorithm that contains deterministic rules for selecting targets and allocating subsidies, achieving a competitive ratio of \(1-O(\epsilon )\) for both settings. Especially, in the single-slot setting, we propose tailored support policies for each advertiser.

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Near-Optimal Algorithm for Supporting Small and Medium-Sized Enterprises in Ad Systems

  • 会议论文

  • 发表日期：

    2025年

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  • Weian Li,
  • Qi Qi,
  • Bingzhe Wang,
  • Tao Xiao,
  • Changyuan Yu

摘要

In this paper, we introduce an online decision model, effectively capturing the features of real-time support in online advertising. We target small and medium-sized enterprise (SME) advertisers, who lack opportunities for exposure, and consider how to provide additional support for them to acquire advertising slots. This paper investigates two settings, single slot and multiple slots. In both scenarios, our objective is to design online support algorithms that maximize the cumulative utility of SMEs across multiple rounds within the fixed support budget. Technically, we propose a dual-based online algorithm that contains deterministic rules for selecting targets and allocating subsidies, achieving a competitive ratio of \(1-O(\epsilon )\) for both settings. Especially, in the single-slot setting, we propose tailored support policies for each advertiser.