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Qi Zhang 0109

dblp:52/323-109 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2023
0000-0002-7635-5970ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Databases, data management, data science and information retrieval · 1 · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
1 paper
Algorithmic game theory and mechanism design · 100%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Computational finance and economics · 100%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Algorithmic game theory and mechanism design › auction theory › advertising auctions
ad auction design
0.712023
Ad Auction Design with Coupon-Dependent Conversion Rate in the Auto-bidding World · WWW 2023
Algorithmic game theory and mechanism design › mechanism design
auction design
0.712023
Ad Auction Design with Coupon-Dependent Conversion Rate in the Auto-bidding World · WWW 2023
Algorithmic game theory and mechanism design › auction theory › bidding strategy
auto-bidding
0.712023
Ad Auction Design with Coupon-Dependent Conversion Rate in the Auto-bidding World · WWW 2023
Algorithmic game theory and mechanism design › mechanism design
incentive compatibility
0.712023
Ad Auction Design with Coupon-Dependent Conversion Rate in the Auto-bidding World · WWW 2023
Computational finance and economics
online advertising
0.212023
Ad Auction Design with Coupon-Dependent Conversion Rate in the Auto-bidding World · WWW 2023

Methods — techniques the papers use, named apart from their topics

pacing equilibrium · 1.3approximation analysis · 1.3
YearPublicationVenuePosition
2023 Ad Auction Design with Coupon-Dependent Conversion Rate in the Auto-bidding World
abstract
Online advertising has become a dominant source of revenue of the Internet. In classic auction theory, only the auctioneer (i.e., the platform) and buyers (i.e., the advertisers) are involved, while the advertising audiences are ignored. For ecommerce advertising, however, the platform can provide coupons for the advertising audiences and nudge them into purchasing more products at lower prices (e.g., 2 dollars off the regular price). Such promotions can lead to an increase in amount and value of purchases. In this paper, we jointly design the coupon value computation, slot allocation, and payment of online advertising in an auto-bidding world. Firstly, we propose the auction mechanism, named CFA-auction (i.e., Coupon-For-the-Audiences-auction), which takes advertising audiences into account in the auction design. We prove the existence of pacing equilibrium, and show that CFA-auction satisfies the IC (incentive compatibility), IR (individual rationality) constraints. Then, we study the optimality of CFA-auction, and prove it can maintain an approximation of the optimal. Finally, experimental evaluation results on both offline dataset as well as online A/B test demonstrate the effectiveness of CFA-auction.
Bonan Ni, Qi Zhang 0109, Pingzhong Tang, Zhourong Chen, Tianjiu Yin, Liangni Lu, Kewu Sun
WWW3