| 基于聚类分析的电子商务推荐系统 |
| |
| 引用本文： | 程岩,肖小云,吴洁倩.基于聚类分析的电子商务推荐系统[J].计算机工程与应用,2005,41(24):175-177. |
| |
| 作者姓名： | 程岩 肖小云 吴洁倩 |
| |
| 作者单位： | 复旦大学管理学院信息管理与信息系统系,上海,200433 |
| |
| 摘 要： | 协同过滤技术可以通过分析客户群共同的消费品味来形成推荐。数据稀缺性问题是协同过滤技术面临的主要挑战。文章利用ROCK聚类算法提出了一种基于协同过滤技术的推荐系统模型,该模型可以有效地解决基于协同推荐的数据稀缺性问题。
|
| 关 键 词： | 电子商务 推荐系统 协同过滤 |
| 文章编号： | 1002-8331-（2005）24-0175-03 |
| 收稿时间： | 2004-11 |
| 修稿时间： | 2004-11 |
E-Commerce Recommendation System Based on Clustering Analysis |
| |
| Cheng Yan,Xiao Xiaoyun,Wu Jieqian.E-Commerce Recommendation System Based on Clustering Analysis[J].Computer Engineering and Applications,2005,41(24):175-177. |
| |
| Authors: | Cheng Yan Xiao Xiaoyun Wu Jieqian |
| |
| Abstract: | Collaborative Filtering(CF) is used for forming recommendation by analyzing the common "taste" shared by a group of customers.Data sparsity problem is a potential challenge of collaborative filtering.In this paper,a CF-based recommendation system model is presented,which attempt to bridge the sparsity problem by incorporating ROCK,a kind of clustering algorithm,into the recommendation system. |
| |
| Keywords: | Electronic Commerce recommendation systems collaborative filtering |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
