摘要
受用户行为和商品属性的影响,线上商品推荐的可靠性难以得到保障,为此,设计基于云计算的线上商品智能推荐系统。将密集计算型ic5云服务器作为系统的硬件装置;在软件设计阶段,利用云计算技术对用户行为进行综合分析,并将其与商品属性进行匹配分析,确定最终的推荐结果。应用测试结果显示,该系统在不同数据集上的接受者操作特性曲线下面积(Area Under Curve,AUC)表现出了较高的稳定性,且均在0.88以上,表明该系统具有较高的应用价值。
Under the influence of user behavior and commodity attribute,it is difficult to guarantee the reliability of online commodity recommendation.Therefore,an online commodity intelligent recommendation system based on cloud computing is designed.The dense computing ic5 cloud server is used as the hardware device of the system;in the software design stage,cloud computing technology is used to comprehensively analyze user behavior and match it with commodity attributes to determine the final recommended results.Application test results show that the Area Under Curve(AUC)of the system on different data sets shows high stability,and all of them are above 0.88,indicating that the system has high application value.
作者
薛丽香
巨筱
XUE Lixiang;JU Xiao(Zhengzhou University of Science and Technology,Zhengzhou Henan 450064,China)
出处
《信息与电脑》
2024年第4期112-114,共3页
Information & Computer
基金
2022年度郑州市社会科学调研课题(项目编号:ZSLX20220138)。
关键词
云计算
线上商品
智能推荐
用户行为
商品属性
cloud computing
online commodity
intelligent recommendation
user behavior
commodity attribute