Fatigue-Aware Ad Creative Selection
원문 초록
In online display advertising, selecting the most effective ad creative (ad image) for each impression is a crucial task for DSPs (Demand-Side Platforms) to fulfill their goals (click-through rate, number of conversions, revenue, and brand improvement). As widely recognized in the marketing literature, the effect of ad creative changes with the number of repetitive ad exposures. In this study, we propose an efficient and easy-to-implement ad creative selection algorithm that explicitly considers user's psychological status when selecting ad creatives. The proposed system was deployed in a real-world production environment and tested against the baseline algorithms. The results show superiority of the proposed algorithm.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
Scalable Subset Selection in Linear Mixed Models
Must Read: A Systematic Survey of Computational Persuasion
Person detection and re-identification in open-world settings of retail stores and public spaces
AI-Slop to AI-Polish? Aligning Language Models through Edit-Based Writing Rewards and Test-time Computation
GNN-Based Candidate Node Predictor for Influence Maximization in Temporal Graphs
Collaborating with AI Agents: Field Experiments on Teamwork, Productivity, and Performance
토론
이 논문과 연결된 포럼 글이 아직 없습니다.