Abstract:
In this paper, we propose a collaborative filtering algorithm based on cosine similarity weight (COSLOPE algorithm). The similarity between the users is calculated by the cosine algorithm; the weights are determined according to the similarity degree and the scoring matrix is filled in order to establish the nearest neighbor set with high similarity to the object user. The nearest neighbor set of the nearest neighbor set is to predict the target user’s project grade and make recommendations. The algorithm is validated by the MovieLens dataset, and the values of MAE, RMSE and MSE are superior to the traditional Slope One algorithm. COSLOPE algorithm is not only in the effective solution of data sparseness, but also improve the accuracy of the traditional recommendation algorithm and reduce the algorithm response time.