research-article

COPR: Consistency-Oriented Pre-Ranking for Online Advertising

Authors:

Xiang-Rong Sheng,

Bo ZhengAuthors Info & Claims

CIKM '23: Proceedings of the 32nd ACM International Conference on Information and Knowledge Management

Pages 4974 - 4980

https://doi.org/10.1145/3583780.3615465

Published: 21 October 2023 Publication History

Abstract

Cascading architecture has been widely adopted in large-scale advertising systems to balance efficiency and effectiveness. In this architecture, the pre-ranking model is expected to be a lightweight approximation of the ranking model, which handles more candidates with strict latency requirements. Due to the gap in model capacity, the pre-ranking and ranking models usually generate inconsistent ranked results, thus hurting the overall system effectiveness. The paradigm of score alignment is proposed to regularize their raw scores to be consistent. However, it suffers from inevitable alignment errors and error amplification by bids when applied in online advertising. To this end, we introduce a consistency-oriented pre-ranking framework for online advertising, which employs a chunk-based sampling module and a plug-and-play rank alignment module to explicitly optimize consistency of ECPM-ranked results. A ΔNDCG-based weighting mechanism is adopted to better distinguish the importance of inter-chunk samples in optimization. Both online and offline experiments have validated the superiority of our framework. When deployed in Taobao display advertising system, it achieves an improvement of up to +12.3% CTR and +5.6% RPM.

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Cited By

Sheng XYang FGong LWang BChan ZZhang YCheng YZhu YGe TZhu HJiang YXu JZheng BSerra ESpezzano F(2024)Enhancing Taobao Display Advertising with Multimodal Representations: Challenges, Approaches and InsightsProceedings of the 33rd ACM International Conference on Information and Knowledge Management10.1145/3627673.3680068(4858-4865)Online publication date: 21-Oct-2024
https://dl.acm.org/doi/10.1145/3627673.3680068

Index Terms

COPR: Consistency-Oriented Pre-Ranking for Online Advertising
1. Information systems
  1. Information retrieval

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cover image ACM Conferences

CIKM '23: Proceedings of the 32nd ACM International Conference on Information and Knowledge Management

October 2023

5508 pages

ISBN:9798400701245

DOI:10.1145/3583780

General Chairs:
Ingo Frommholz
University of Wolverhampton, UK
,
Frank Hopfgartner
University of Koblenz, Germany
,
Mark Lee
University of Birmingham, UK
,
Michael Oakes
University of Birmingham, UK
,
Program Chairs:
Mounia Lalmas
Spotify, UK
,
Min Zhang
Tsinghua University, China
,
Rodrygo Santos
Federal University of Minas Gerais, Brazil

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Published: 21 October 2023

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October 21 - 25, 2023

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Cited By

Sheng XYang FGong LWang BChan ZZhang YCheng YZhu YGe TZhu HJiang YXu JZheng BSerra ESpezzano F(2024)Enhancing Taobao Display Advertising with Multimodal Representations: Challenges, Approaches and InsightsProceedings of the 33rd ACM International Conference on Information and Knowledge Management10.1145/3627673.3680068(4858-4865)Online publication date: 21-Oct-2024
https://dl.acm.org/doi/10.1145/3627673.3680068

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