Online Advertising

Online advertising aims to optimize the delivery and effectiveness of advertisements, primarily focusing on maximizing advertiser return on investment (ROI) and platform revenue while enhancing user experience. Current research emphasizes improving prediction models (e.g., using deep learning, factorization machines, and ensemble methods) for key metrics like click-through rates (CTR) and conversion rates (CVR), often incorporating techniques like self-supervised pre-training and multi-field calibration to address data sparsity and improve accuracy. These advancements are significant because they directly impact the efficiency and profitability of online advertising platforms and the effectiveness of marketing campaigns for businesses.