摘要
字节跳动的广告推荐系统中应用了高级的人工智能算法,以实现个性化的广告投放。系统结构包括数据层、服务层和应用层,通过这一结构处理大规模数据,并实现快速的算法迭代。本文详细讨论了算法的基础原理、架构及评估指标,并探究了特征工程优化、模型融合技术和实时推荐算法的应用。实际案例分析展示了系统在提高广告效率和用户满意度方面的实际成效,同时指出了在实施过程中遇到的挑战及应对策略。
Advanced AI algorithm is applied in the advertising recommendation system with ByteDance to realize personalized advertising.The system architecture includes a data layer,a service layer,and an application layer,through which large-scale data is processed and fast algorithm iterations are achieved.This article discusses in detail the basic principles,architecture,and evaluation indicators of algorithms,and explores the applications of feature engineering optimization,model fusion techniques,and real-time recommendation algorithms.The practical case analysis demonstrates the actual effectiveness of the system in improving advertising efficiency and user satisfaction,while pointing out the challenges and response strategies encountered in the implementation process.
作者
母亦翔
MU Yixiang(Beijing Zitiao Network Technology Co.,Ltd.,Beijing 100089,China)
出处
《数字通信世界》
2025年第6期62-64,共3页
Digital Communication World
关键词
个性化推荐
算法优化
实时数据处理
personalized recommendation
algorithm optimization
real time data processing
作者简介
母亦翔(1984-),男,汉族,天津人,硕士研究生,研究方向为人工智能、算法技术的广告应用。
