PAN Feng,HUAI Libo*,CUI Rongyi.Research on SVD collaborative filtering recommender algorithm fused items’ attribute feature[J].Journal of Yanbian University,2017,43(04):334-338.
融合项目属性特征的SVD协同过滤推荐算法研究
- Title:
- Research on SVD collaborative filtering recommender algorithm fused items’ attribute feature
- 分类号:
- TP391
- 文献标志码:
- A
- 摘要:
- 针对协同过滤方法中用户-项目评分矩阵的极端稀疏性问题,提出了一种基于层次的混合推荐方法.首先利用TF-IDF提取项目属性特征,并利用余弦相似度对评分矩阵的缺失值进行填充; 然后通过对填充的矩阵做SVD,寻找隐性特征,建立隐语义模型; 最后将本文的算法分别与众数填充和无填充模型进行对比实验,结果表明本文提出的方法有效提高了推荐的精度.
- Abstract:
- In this paper, a hierarchy-based hybrid recommendation method algorithm is proposed for the sparsity problem of user-item rating matrix in collaborative filtering. Firstly, this algorithm extracted the attributes of items by using TF-IDF method, and filled the missing values with cosine similarity in ratings matrix. Then, the latent factor model was established by doing SVD for the filled matrix to find the latent feature. At last, the compared experiment was carried on with mode-filling and non-filling model. The experiment results show that the proposed algorithm can improve the recommended accuracy.
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备注/Memo
收稿日期: 2017-06-23 基金项目: 吉林省科技计划项目(20140101186JC)*通信作者: 怀丽波(1973—),女,副教授,研究方向为优化理论与方法、数据挖掘.