针对用户在社区网络中面对海量的信息和资源，如何快速便捷地获得自己感兴趣内容的问题，提出一

种基于社区网络内容的个性化推荐算法。在得到相同兴趣用户聚类的基础上，该算法首先通过用户访问日志信

息挖掘相似内容推荐项，然后根据用户兴趣挖掘新的内容推荐项。实验结果表明，该算法不仅提高了内容推荐

精度，而且扩展了内容覆盖面。-Network for users in the community in the face of a flood of information and resources, how to quickly and easily access content of interest issue, a

Kinds of community-based web content personalized recommendation algorithm. Users get the same interest in the cluster, based on the algorithm begins with the user access log information

Information content of recommended items similar to mining, and mining based on user interest in new content recommended items. Experimental results show that the algorithm not only improve the content recommended

Accuracy, and extend the content coverage.