电子商务平台中的个性化推荐系统与用户黏性分析  

Analysis of Personalized Recommendation Systems and User Stickiness in E-Commerce Platforms

作　　者：李梓铭 LI Ziming(Krirk University,Bangkok 999003,Thailand)

机构地区：[1]格乐大学,泰国曼谷999003

出　　处：《商业观察》2025年第4期39-42,共4页BUSINESS OBSERVATION

摘　　要：在电子商务平台中,个性化推荐系统是提升用户体验和增强用户黏性的关键技术。文章系统分析了个性化推荐系统的基本原理、架构和实现方法,探讨了用户黏性的定义、影响因素及提升策略。通过研究个性化推荐系统对用户行为、满意度和黏性的具体影响,结合案例分析,对个性化推荐系统的实际应用效果进行了评估,并提出了个性化推荐系统的优化与改进策略,包括算法优化、数据处理技术提升以及用户隐私保护等方法,以期通过个性化推荐系统的有效应用,进一步提高用户黏性。In e-commerce platforms,personalized recommendation systems are key technologies for improving user experience and increasing user stickiness.This article systematically analyzes the basic principles,architecture,and implementation methods of personalized recommendation systems,and explores the definition,influencing factors,and improvement strategies of user stickiness.By studying the specific effects of personalized recommendation systems on user behavior,satisfaction,and stickiness,combined with case analysis,the effectiveness of personalized recommendation systems in practical applications is evaluated,and optimization and improvement strategies for personalized recommendation systems are proposed,including algorithm optimization,data processing technology improvement,and user privacy protection and other methods,in order to further enhance user stickiness through personalized recommendation systems.

关 键 词：电子商务平台 个性化推荐系统 用户黏性 推荐算法 数据隐私 

分 类 号：F713.36[经济管理—产业经济] TP391.3[自动化与计算机技术—计算机应用技术]