考虑MeanShift用户聚类的云服务推荐  

Cloud Service Recommendation Considering Meanshift User Clustering

作　　者：王著鑫 耿秀丽[1] 王龙羽 王婉婷 WANG Zhu-xin;GENG Xiu-li;WANG long-yu;WANG wan-ting(Business School,University of Shanghai for Science and Technology,Shanghai 200093,China)

机构地区：[1]上海理工大学管理学院,上海200093

出　　处：《软件导刊》2022年第4期169-176,共8页Software Guide

基　　金：国家自然科学基金项目(71301104);教育部人文社会科学研究规划基金项目(19YJA630021);高等学校博士学科点专项科研基金项目(20133120120002)。

摘　　要：针对传统云服务推荐算法只考虑推荐精度而忽略推荐效率问题,提出考虑了MeanShift用户聚类的云服务推荐。MeanShift聚类算法计算量小、运行速度快,可对任意分布的数据进行密度估计。该云服务首先根据数据密度分布对所有用户进行访问,然后计算用户在各个类簇中出现的累计频数,并将其划分到累计频数最大的类簇中,最后在该类簇中寻找目标用户的近邻集用于推荐云服务。样本推荐结果显示:与信任云推荐算法、信任云混合推荐算法、基于灰色关联与信任云混合算法相比,该算法在平均绝对误差上降低约10.15%,在均方根误差上降低约7.87%,在执行时间上降低约59.77%,说明所提算法在保证一定推荐精度的基础上有效提高了推荐效率。Aiming at the problem that traditional cloud service recommendation algorithm only considered the recommendation precision but ignored the recommendation efficiency,the cloud service recommendation algorithm considering MeanShift user clustering is proposed.Mean⁃Shift clustering algorithm requires a little computation,runs fast and can estimate the density of arbitrary distributed data.The cloud service recommendation algorithm first accesses all users according to the data density distribution.Then it calculates the cumulative frequency of us⁃ers in each class cluster and puts respectively them into the class cluster with the largest cumulative frequency.Finally,the nearest neighbor set of the target user in the class cluster can be used for recommending cloud services.The sample recommendation results show that the pro⁃posed algorithm reduces mean absolute error by about 10.15%,compared with the trust-cloud recommendation algorithm,trust-cloud hybrid recommendation algorithm,and the hybrid algorithm based on grey correlation and trust-cloud.The root-mean-square error was decreased by about 7.87%.The execution time was reduced by about 59.77%.It shows that the proposed algorithm can effectively improve the recommenda⁃tion efficiency on the basis of ensuring certain recommendation accuracy.

关 键 词：云服务推荐 MEANSHIFT 灰色关联预测 信任云 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]