基于USDR模型的云推荐方法研究

Research on cloud recommendation method based on USDR model

摘要:

在云环境中,对于云数据的统一建模一直是研究热点。尤其在推荐系统中,对于多源异构数据灵活性和安全性的要求更高。随着数据信息技术的不断发展,网络更新逐步加快,数据的更新也越来越快,从海量信息中如何快速帮助用户获取偏好的信息变得更加困难。针对多源异构数据的特征,综合移动互联网安全性和隐私性等特点,提出了一种USDR模型,并在该模型的基础上对云环境中的推送方法进行了研究,主动帮助用户发现自己偏好的信息,并将这些信息展现给可能需要的用户,并且实现了传统的数据推荐方法无法处理的多源异构数据的云推荐。根据云推送平台在实验环境中的运行情况及相关指标分析,说明该云推荐方法能适用于多源异构数据的推荐,是一种高效可行的推荐方法。

Abstract:

In the cloud environment, the unified modeling of cloud data has been a hot research topic. In particular, the requirement for flexibility and security of multi-source heterogeneous data is higher. With the continuous development of data and information technology, the gradual acceleration of network updates, data updates are also getting faster and faster, from the mass of information on how to quickly help users get the preference of information becomes more difficult. According to the characteristics of heterogeneous data, comprehensive mobile Internet Security and privacy features proposed a USDR model, and on the basis of the model of cloud environment in the push method were studied, take the initiative to help users find their preference information and will show users may need the information, and to achieve the recommended that cannot be handled by traditional methods of data recommended multi-source heterogeneous data cloud. According to the operation condition and related indexes of cloud push platform in experiment environment, it is suggested that the cloud recommendation method can be applied to multi-source heterogeneous data, and it is a highly efficient and feasible recommendation method.