摘要
本文探讨了个性化推荐系统的研究背景、意义、设计、实现及其应用价值。随着大数据和AI技术的发展，个性化推荐系统成为提升用户体验和用户粘性的关键。文章分析了个性化推荐在多个领域的现状和挑战，概述了推荐系统的定义、分类和核心要素，如用户画像、物品特征和推荐算法，并详细描述了推荐流程。接着，文章重点设计了推荐系统的架构，包括需求分析、系统设计、推荐策略和用户体验设计。实现阶段介绍了开发环境、数据处理、推荐引擎和前端界面的实现，以及系统测试和性能调优。本文构建了个性化推荐系统框架，并通过实践验证了其有效性和可行性，对提升推荐系统精准度和用户体验具有重要意义。未来，个性化推荐系统将随着技术进步和用户需求变化而持续演进，为更多领域提供智能、高效的推荐服务。
关键词 个性化推荐系统,推荐算法；用户体验；系统实现
Abstract
This paper discusses the research background, significance, design, implementation and application value of personalized recommendation system. With the development of big data and AI technology, personalized recommendation systems have become the key to improving user experience and user engagement. This paper analyzes the current situation and challenges of personalized recommendation in many fields, outlines the definition, classification and core elements of the recommendation system, such as user portrait, item characteristics and recommendation algorithm, and describes the recommendation process in detail. Then, the article focuses on designing the architecture of the recommendation system, including requirements analysis, system design, recommendation strategy and user experience design. The implementation phase introduces the development environment, data processing, implementation of the recommendation engine and front-end interface, as well as system testing and performance tuning. This paper constructs the fr amework of personalized recommendation system, and verifies its effectiveness and feasibility through practice, which is of great significance to improve the accuracy and user experience of the recommendation system. In the future, the personalized recommendation system will continue to evolve with the technological progress and the change of user needs, providing intelligent and efficient recommendation services for more fields.
Keywords Personalized recommendation system, Recommendation algorithm; User experience; System implementation
目录
摘要 I
Abstract II
第1章 绪论 1
1.1 研究背景及意义 1
1.2 国内外研究现状 1
第2章 相关理论概述 2
2.1 个性化推荐的定义与分类 2
2.2 个性化推荐的核心要素 2
第3章 个性化推荐系统的设计 4
3.1 需求分析 4
3.2 系统架构设计 5
3.3 推荐策略与算法设计 6
3.4 用户体验与交互设计 7
第4章 个性化推荐系统的实现 8
4.1 开发环境与工具选择 8
4.2 系统核心模块实现 9
4.3 前端界面与交互实现 10
4.4 系统测试与部署 11
结论 12
参考文献 13
致谢 14
