基于用户兴趣的协同过滤推荐算法研究

Collaborative filtering recommendation algorithm based on user interest

针对现有系统过滤算法在用户兴趣、数据稀疏性方面的不足,提出一种基于用户兴趣的协同过滤推荐算法.该算法引入用户兴趣权重,建立用户-项目评价矩阵,通过聚类分析进行相似性计算,最终得到推荐结果.实验结果表明,本算法能有效地利用用户兴趣,提高推荐质量.

In view of the problem with insufficient of the users interest,data sparsity in filter algorithm system,a collaborative filtering recommendation algorithm based on users interest was proposed. The algorithm introduced the user interest weights,established evaluation user-item matrix,through cluster analysis,makes similarity calculation and finally got the recommended results. The experimental results showed that the algorithm could effectively use the interest of user,and improve the quality of recommendation.