针对用户在Web多人协作平台中面对海量的信息和资源,如何快速便捷地获取自己感兴趣的内容问题,提出一种基于用户特征的个性化推荐算法.在提取出用户特征的基础上,该算法首先通过计算特征的相似性找出目标用户的最近k个邻居,然后由最近邻居的内容推荐项得到目标用户的推荐项.实验结果表明,该算法能够很好地应用于Web多人协作平台.%Based on the issue that how to acquire the interesting information for users quickly and effectively from massive data, this paper proposes a personalized recommendation algorithm based on user characteristics in Web multi-cooperation platform. On the basis of extracting user characteristics, firstly through calculates the similarity of characteristic to find target user' s nearest k neighbor, then obtains the target user's recommendation item based on the nearest neighbor' s recommendation content. The experimental results show that this algorithm can applicate in Web multi-cooperation platform effectively.
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