关键词: 个性化推荐, K-means聚类算法, 动态多维网络

Abstract:

A network resource personalized recommendation method based on K-means clustering algorithm is presented for dynamic multidimensional social network. Firstly, the user is modeled according to the user rating data, and a multidimensional network is constructed by collecting all the users' rating data, and then a dynamic multidimensional network could be formed with the help of local world evolving network model. Secondly, the network users are clustered by using the improved K-means algorithm. Finally, the objective user's rating could be forecasted and obtained by referring the nearest neighbors, and the personalized recommendations could be made. So far, a network resource personalized recommendation method suitable for dynamic multidimensional social network is formed. The experimental results show that the new recommendation method could reduce the error between the prediction value and the true value by comparing with the collaborative filtering recommendation system, and hereby, the new recommendation method could achieve the improved personalized recommendations.

Key words: personalized recommendations, K-means clustering algorithm, dynamic multidimensional network