arXiv:2605.21556v1 Announce Type: new Abstract: Guaranteed display advertising is crucial for platform monetization, yet existing methods often operate under a single-slot assumption, limiting their ability to optimize allocation across multi-slot page views. In this paper, we propose a novel joint optimization framework for multi-slot GD allocation, addressing key challenges such as slot-level redundancy, contract imbalance, and exposure concentration. Our approach formulates the allocation as an offline bipartite matching problem with a contract roulette mechanism for slot exclusivity and Pa
The continuous evolution of AI and optimization techniques, coupled with increasing complexity in online advertising platforms, drives the need for more sophisticated allocation models.
Improved multi-slot advertising optimization can significantly enhance platform monetization and advertiser ROI, impacting the economics of digital content distribution and AI-driven ad tech.
This research suggests a move from single-slot to multi-slot optimization in display advertising, potentially leading to more efficient ad placements and higher revenue for platforms.
- · Ad platforms (e.g., Google, Meta)
- · Advertisers leveraging AI-driven budget allocation
- · Ad-tech companies
- · Consumers (potentially, through better ad experiences)
- · Ad platforms with outdated allocation models
- · Advertisers without sophisticated bidding/allocation engines
More efficient and profitable display advertising campaigns for platforms and advertisers.
Increased competition and innovation in the ad-tech sector as companies adopt or develop multi-slot optimization capabilities.
Potential for enhanced user experience in ad-supported digital environments if allocation improves ad relevance.
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Read at arXiv cs.LG