提出基于二部网络连接预测的推荐算法. 将用户-项目的评分矩阵用带权的二部网络来表达,根据推荐问题和带权二部网络连接预测问题的相似性将推荐问题抽象为二部网络上的链接预测问题,采用基于相似度的连接预测算法进行项目推荐. 算法综合考虑了顶点间的拓扑关系,以及用户之间、项目之间的相似性,找出用户对其尚未表达的项目的潜在兴趣度,应用二部网络连接预测的算法来解决推荐问题. 实验结果表明,算法能够有效地提高推荐的精度.An algorithm for recommendation based on link prediction in a bipartite network is presented. We use a weighted bipartite network to represent the user-item matrix. Due to the similarity between recommendation and link prediction in bipartite network,we transform the recommendation into the problem of link prediction in bipartite network. The similarity based method is used to predict the potential links considering the topological similarity between the nodes in the network,the similarity between users and the similarity between the items. The potential interests of the users to the items can be found by link prediction in the bipartite network. Our experimental results show that our algorithm can get high recommendation results
