This paper puts forward an model based on classify in collaborative filtering.
在协同过滤中，提出基于分类的协同过滤算法。
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。
Collaborative filtering algorithm based on model users greatly improves the efficiency of online recommendation, makes model users relatively stable and also improves the accuracy of recommendation.
对在此基础上生成的模范用户模型应用协同过滤推荐算法，目标用户在线推荐的效率有很大的提高，模范用户模型相对稳定，推荐精度也有所改善。
Collaborative filtering can be divided into memory based and model based. The former is more accurate while the latter performs better in scalability.
协同过滤技术分为基于内存和基于模型两种，前者的推荐准确度更高，但可扩展性比后者低。
Collaborative filtering can be divided into memory based and model based. The former is more accurate while the latter performs better in scalability.
协同过滤技术分为基于内存和基于模型两种，前者的推荐准确度更高，但可扩展性比后者低。
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