一种物联网协同过滤QoS预测与服务推荐方法  

A Collaborative Filtering QoS Prediction and Service Recommendation Method for Internet of Things

作　　者：杨怀洲[1] 张留美[1] 

机构地区：[1]西安石油大学计算机学院,西安710065

出　　处：《计算机工程》2016年第11期1-7,共7页Computer Engineering

基　　金：陕西省教育厅科研计划项目(14JK1585);西安市科技计划项目(CXY1437(7))

摘　　要：针对物联网软硬件功能不断服务化以及服务质量(QoS)难以预测的问题,提出一种物联网QoS预测与服务推荐方法。根据用户服务调用与服务QoS历史使用信息,结合基于用户和基于项目的协同过滤方法进行用户项目矩阵缺失值预测,将稠密化后的用户项目矩阵作为当前用户预测相关服务的QoS值,并基于该QoS值预测结果实现服务选择与推荐。通过一个大规模实测服务调用QoS数据集验证了该方法的有效性,实验结果表明其具有较高的预测精度,适用于物联网服务选择与推荐。Aiming at the problems that more and more software and hardware functions of Internet of Things（IoT）are provided as services,and the Quality of Service（QoS）of IoT services is difficult to predict,a method of QoS prediction and service recommendation for IoT network is presented.Based on the historical usage data of service invocations and their QoS,the missing values of the user-item matrix are predicted by combining the user-based and item-based collaborative filtering approaches.The QoS values of services are predicted for the active users by the densified user-item matrix.Furthermore,the prediction results are used to realize effective service selection and recommendation.The presented method is validated by taking advantage of a large-scale data set of real service invocations.The experimental result indicates that better prediction accuracy can be obtained through the method,and it is suitable for IoT service selection and recommendation.

关 键 词：物联网 协同过滤 服务质量预测 服务选择 服务推荐 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]