摘要
为了提升云计算平台的个性化推荐服务,文章采用了大数据分析与智能推荐算法相结合的方法,分析了云计算平台智能推荐系统的设计与实现。通过深度挖掘用户行为数据与兴趣偏好,优化推荐算法,结合分布式计算与存储架构,能够实现高效的个性化推荐。结果表明,该系统能够在实时数据处理与精准推荐方面取得显著效果,极大提升平台用户体验与粘性,为后续技术创新提供可行路径。
In order to enhance the personalized recommendation service of cloud computing platform,the article adopts the method of combining big data analysis and intelligent recommendation algorithm,and analyzes the design and implementation of intelligent recommendation system for cloud computing platform.By deeply mining user behavior data and interest preferences,optimizing recommendation algorithms,and combining distributed computing and storage architecture,efficient personalized recommendations can be achieved.The results show that the system can achieve significant results in real-time data processing and accurate recommendation,greatly improving the platform user experience and stickiness,and providing a feasible path for subsequent technological innovation.
作者
杨柳
贾彦玲
宋志阳
程宇
YANG Liu;JIA Yanling;SONG Zhiyang;CHENG Yu(Anyang University,Anyang Henan 455000,China;Anyang Secondary Vocational and Technical School,Anyang Henan 455000,China)
出处
《信息与电脑》
2025年第2期37-39,共3页
Information & Computer
关键词
云计算
智能推荐系统
大数据分析
cloud computing
intelligent recommendation system
big data analysis
