面向移动客户端的数据服务推荐策略研究

Scheme of Data Service Recommendation for Mobile Devices

将移动设备所具有的随时随地、灵活按需的特点和云平台中的海量数据和服务无缝集成已成为云计算和移动计算共同的研究热点.在移动客户端上进行数据服务的推荐,可以减少用户在狭小的屏幕空间上进行浏览和选取带来的不便.同时,将位置信息作为推荐的依据可以增加推荐的准确性.提出一种面向移动客户端的数据服务推荐策略,综合使用图论模型、协同过滤模型等方法来进行推荐,可以支持移动用户快速准确地找到自己需要的数据服务.通过实例验证表明,该策略可以有效提高用户获取服务的效率,改善用户体验.

Cloud computing and mobile computing share one popular research point：combining the flexibility of mobile devices and numerous data services of cloud platforms together. Data service recommendation on mobile devices will alleviate the inconvenience when browsing and selecting on a cramped screen. At the same time, considering location information will increase the accuracy of recommendation. On the basis of graph theory and collaborative filtering,this paper puts forward a data service recommendation scheme for mobile devices to help mobile users find needed services accurately. Application examples show that this approach can effectively increase the efficiency of service obtaining and improve the user experience.