CVR Prediction

Conversion rate prediction (CVR prediction) aims to accurately forecast the likelihood of a user completing a desired action, such as a purchase or click. Current research focuses on addressing challenges like delayed feedback, data scarcity in specific scenarios (e.g., small-scale e-commerce), and handling diverse data types and contexts. This involves developing sophisticated models, including graph neural networks for handling temporal dependencies and meta-learning approaches for adapting to fluctuating data distributions, as well as exploring efficient architectures like multi-domain networks to handle multiple scenarios simultaneously. Improved CVR prediction has significant implications for optimizing online advertising, recommendation systems, and other applications requiring accurate user behavior forecasting.