| 基于Web挖掘的电子商务推荐系统中推荐方法研究 |
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| 引用本文： | 景丽,黄献波. 基于Web挖掘的电子商务推荐系统中推荐方法研究[J]. 郑州轻工业学院学报(自然科学版), 2006, 21(4): 66-68 |
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| 作者姓名： | 景丽 黄献波 |
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| 作者单位： | 1. 河南财经学院,信息学院,河南,郑州,450002
2. 河南财经学院,基建处,河南,郑州,450002 |
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| 基金项目： | 河南省教育厅自然科学基金资助项目(2004922081) |
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| 摘 要： | 以改进Apriori算法、K_means聚类算法和ARHP算法3种不同的Web挖掘技术为基础构造推荐算法,形成推荐集.仿真实验结果表明基于ARHP的推荐算法的覆盖率和准确度明显高于其他两种方法,可用于基于Web挖掘的电子商务推荐系统中.
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| 关 键 词： | 电子商务 推荐系统 推荐方法 Web挖掘 协同过滤 事务聚类 关联规则 关联规则超图划分技术 |
| 文章编号： | 1004-1478（2006）04-0066-03 |
| 收稿时间： | 2006-10-16 |
| 修稿时间： | 2006-10-16 |
Study on the recommending methods used in e-commerce recommending system based on Web usage mining |
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| JING Li,HUANG Xian-bo. Study on the recommending methods used in e-commerce recommending system based on Web usage mining[J]. Journal of Zhengzhou Institute of Light Industry(Natural Science), 2006, 21(4): 66-68 |
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| Authors: | JING Li HUANG Xian-bo |
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| Affiliation: | 1, College of lnfor., Henan Univ. of Finance and Econo., Zhengzhou 450002, China; 2. Dept. of Capital Construction, Henan Univ. of Finance and Econo. , Zhengzhou 450002, China |
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| Abstract: | In research about recommendation system in e-commerce based on web usage mining,three recommending methods based on improved technique about Apriori, K-means cluster way and ARPH technique are presented.In the testing we find the precision and coverage rates of the recommending method based on ARHP outperform the other two methods obviously,which can be utilized in the e-commerce recommendation system. |
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| Keywords: | e-commerce recommending system recommending method Web usage mining collaborative filtering algorithm transaction clustering association rule ARHP |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
