Approach of neighbor selection based on user classification incollaborative filtering recommendation
协同过滤推荐中基于用户分类的邻居选择方法

In order to improve the quality of recommendation results, selecting proper neighbors would be the important link in collaborative filtering. The user might be divided into three types, which was expertise, trustworthy and similarity, since there were differences between neighbors, the important of them could be differentiated from target users. As the target user, the importance and weight of these three types of neighbors would be analyzed by the method of ridge regression. As a result, the proper neighbors might be found for the target user. According to comparative experiments based on F1 method, it shows that the accuracy has been improved significantly. Meanwhile, through the K-means cluster analysis and LSDleast-significant difference, the result coincides with behavior research's.