Collaborative Filtering Recommendation Model Based on Normalization Method

In view of traditional collaborative filtering recommendation does not take into account differences of dimension of user vector and value of evaluation, this paper proposed a collaborative filtering recommendation model based on normalization method. Before calculating the users or items similarity, the value of evaluation will be normalized to a range of specifications. Then the similarity of user vector will be calculated, and predictions and recommend will be made. The experimental results show that this model could accurately find similar neighbor users or items, and performances of prediction and recommendation have been largely improved.