推荐系统中协同过滤技术的研究

Research on collaborative filtering technology in recommendation system

目前推荐系统中应用最为成熟的技术为协同过滤推荐技术,但是随着用户和资源数量的日益增多,协同过滤推荐技术的问题愈发明显。数据稀疏性是实尚未解决的问题,本文通过在计算相似性时考虑到项目的重复因素,提出了一种优化后的协作推荐算法。最后通过实验证明了优化后算法的有效性。

Currently the most mature application technology of recommended system is collaborative filtering recommendation technology.But as the number of users and resources increasing,collaborative filtering technology is becoming an obvious problem.Data sparseness is one of the unresolved issues.In this paper,the similarity in the calculation of the project taking into account there peated factor.And a optimized collaborative recommendation algorithm is proposed.The experimental results demonstrate the effective of the optimization algorithm.