针对现有推荐算法同等看待每个用户评价信息的问题, 提出一种面向智慧社区的基于可信联盟的服务推荐算法.引入用户的信誉度和服务使用频率, 改进传统相似度计算公式, 建立基于用户信任模型的信任关系.在此基础上, 面向智慧社区用户, 引入社区因子, 构建可信联盟, 从而对目标用户进行个性化推荐.实验结果表明, 与基于云模型的链式推荐等算法相比, 该推荐算法的精确度更优.%Aiming at the problem that the existing recommendation algorithms treat each user's evaluation information equally, a service recommendation algorithm based on trusted alliance for intelligent community is proposed. By introducing user reputation and service usage frequency, the traditional similarity calculation formula is improved, and the trust relationship based on user trust model is established. On this basis, the community factor is introduced and the trusted alliance is constructed for the intelligent community users, and then the personalized recommendation for the target users is carried out. Experimental results show that the accuracy of the proposed algorithm is better than that of the chain recommendation algorithm based on cloud model.
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