Research on Cross-Platform Digital Advertising User Behavior Analysis Framework Based on Federated Learning

Abstract

K e y w o r d s A b s t r a c t Cross-Platform Digital Advertising, Federated Learning, Privacy-Preserving Computing, User Behavior Analysis This information is released over the digital movement based on behavioral courses for user assessment. The framework is important to challenge the privacy-keeping the data division and manipulation throughout the platform announced. The network network architecture is designed to detect users of behavioral behavior when keeping personal information from secure. The framework implements an adaptive model aggregation strategy with dynamic weight adjustment mechanisms to optimize cross-platform model performance. Special protection, including special data and homomorphic encryption, has been integrated with security data during training and competition level. Tests have followed our greatest datase in the world, completed for a pre-commitment, the proposed efforts Over 200 million users across 5 million users when maintaining strategic warranty. Assessmental evaluation of significant improvements in advertisement, including the pronouncement (CTR), when minimized time %. The framework procedures for privacy personally used to investigate the characteristics of new ecosystem.