1 相关工作 目前，研究人员提出了各种方案的协同过滤推荐算法 （collaborative filtering recommendation algorithm）：基于用户 （userbased）的协同过滤算法 [1] ，利用不同用户在相同项目上的 评分相似性来推荐k 个最邻居的资源。
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A collaborative filtering recommendation algorithm based on the item features model is proposed in this paper.
提出一种基于项目特征模型的协同过滤推荐算法。
Furthermore, the results show that the accuracy of algorithm proposed here has somewhat increased compared with that of the collaborative filtering recommendation algorithm based on item.
实验结果表明，该算法比基于项目的协同过滤推荐算法在精确度上有所提高。
This paper proposes a collaborative filtering recommendation algorithm based on trust mechanism. Direct trust is based on common rating data and indirect trust is based on the predict data.
提出一种基于信任机制的协同过滤推荐算法，其中，直接信任度基于共同评价项目得出，推荐信任度通过对项目的预测得出。
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