作　　者： ; ; ; ; ;

机构地区： 信息科学与技术学院

出　　处： 《合肥工业大学学报（自然科学版）》 2013年第4期420-424,共5页

摘　　要： 有效的潜在好友推荐是促进社交网络不断增长的重要途径,对于大规模社交网络环境下的复杂计算问题,文章提出了一种适用于大规模社交网络的潜在好友推荐方法,该方法首先将用户的潜在好友划分为"可能认识的"和"可能感兴趣的"2类,然后分别基于用户共同好友关系拓扑图和Profile文本相似性计算模型进行描述,最后基于MapReduce云计算模型对相关方法进行了设计实现。探讨了云计算环境下的潜在好友推荐系统框架设计、大规模用户共同好友关系拓扑图以及Profile文本相似性计算的方法,并通过实验以及应用实例验证了该方法的有效性以及可扩展性。 The effective method for potential friend recommendation can accelerate the growth of social network, but it faces the problem of complicated computation under the environment of large-scale so- cial network. Therefore, a method suitable for making potential friend recommendation based on large-scale social network is proposed. This method firstly divides potential friends into two types-- whom maybe you know and whom maybe you are interested, which are described respectively by using user common friends relation topology and Profile similarity computing. Then the related functions are implemented by using MapReduce cloud computing model. The system framework of potential friend recommendation and the method for large-scale user common friends topology and Profile simi- larity computing are also discussed. The related experiments and application cases have proved that the method is effective and has good extensibility.

关 键 词： 好友推荐 社交网络 文本相似度 云计算模型

领　　域： [自动化与计算机技术] [自动化与计算机技术]