| 一种基于粗集的协同过滤算法 |
| |
| 引用本文： | 张巍,刘鲁,葛健. 一种基于粗集的协同过滤算法[J]. 小型微型计算机系统, 2005, 26(11): 1971-1974 |
| |
| 作者姓名： | 张巍 刘鲁 葛健 |
| |
| 作者单位： | 北京航空航天大学,经济管理学院,北京,100083 |
| |
| 基金项目： | 国家自然基金（70371004）资助. |
| |
| 摘 要： | 针对协同过滤中的数据稀疏问题，提出了一种基于粗集的协同过滤算法．首先通过自动填补空缺评分降低数据稀疏性；然后采用分类近似质量计算用户闻的相似性形成最近邻居，产生推荐预测．实验结果表明，该算法有效地解决了数据稀疏问题，提高了推荐的质量．
|
| 关 键 词： | 协同过滤 数据稀疏 粗集 分类近似质量 |
| 文章编号： | 1000-1220（2005）11-1971-04 |
| 收稿时间： | 2004-06-08 |
| 修稿时间： | 2004-06-08 |
Collaborative Filtering Algorithm based on Rough Set |
| |
| ZHANG wei,LIU lu,GE Jian. Collaborative Filtering Algorithm based on Rough Set[J]. Mini-micro Systems, 2005, 26(11): 1971-1974 |
| |
| Authors: | ZHANG wei LIU lu GE Jian |
| |
| Affiliation: | School of Economics and Management, Beihang University, Beijing 100083, China |
| |
| Abstract: | Aiming at the problem of data sparsity for collaborative filtering, a novel rough set-based collaborative filtering algorithm is proposed. This algorithm addresses the issue by automet.ically filling vacant ratings, uses the quality of approximation of classification to compute user similarity and form nearest neighborhood, and then generates recommendations. The experiment results argue that the algorithm efficiently improves sparsity of rating data, and promises to make recommendations more accurately than conventional CF algorithms. |
| |
| Keywords: | collaborative filtering data sparsity rough set quality of approximation of classification |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
