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中文摘要：
为实现大数据场景下高效、可信的服务推荐,将社交网络理论和信任理论的研究成果有机融合,提出了大数据场景下基于可信社团的服务推荐方法.首先,利用现有的信任模型理论研究成果建立用户间的信任关系,计算用户对服务提供者的信任度;其次,在大数据场景下利用信任关系构建用户可信社团,确定社团中新用户的加入、甄别并删除恶意用户的方法;最后,在构建的可信社团基础上,利用MapReduce框架提出大数据场景下的基于可信社团的服务推荐方法.仿真实验结果表明：提出的方法适用于大数据场景,与传统的服务推荐方法相比,具有更好的性能.
英文摘要：
Aiming at effective and trustworthy service recommendation in big data environments,a service recommendation method based on trustworthy community under big data environments was proposed with integration of social network theories and trust theories.Trust relationship was firstly established based on available trust models and trust of users on service providers was calculated.With construction of trust relationship,trustworthy community was then built,including the addition of new users,and recognition and deletion of malicious users.A service recommendation method based on the trustworthy community was finally proposed with the employment of MapReduce.Simulation results show that the proposed method can be used in big data environments and has better performance compared with other traditional recommendation methods.
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