J4 ›› 2013, Vol. 51 ›› Issue (02): 267-272.

• 计算机科学 • 上一篇    下一篇

基于Web日志挖掘的网页推荐方法

解男男1, 胡亮1, 努尔布力2, 樊丽1, 印晓天3   

  1. 1. 吉林大学 计算机科学与技术学院, 长春 130012; 2. 新疆大学 信息科学与工程学院, 乌鲁木齐 830046;3. 公安部第一研究所| 北京 100048
  • 收稿日期:2012-01-20 出版日期:2013-03-26 发布日期:2013-03-27
  • 通讯作者: 努尔布力 E-mail:nurbol_mail@163.com

Web Recommender System Based on Web Log Mining

XIE Nannan1, HU Liang1, Nurbol2, FAN Li1, YIN Xiaotian3   

  1. 1. College of Computer Science and Technology, Jilin University, Changchun 130012, China;2. College of Information Science and Engineering, Xinjiang University, Urumqi 830046, China;3. The First Research Institute of the Ministry of Public Security of P.R.C., Beijing 100048, China
  • Received:2012-01-20 Online:2013-03-26 Published:2013-03-27
  • Contact: Nurbol E-mail:nurbol_mail@163.com

摘要:

针对传统单纯聚类算法实现网页推荐精确度欠缺的问题, 提出一种基于Web日志挖掘的个性化网页推荐模型, 并实现了相应的网页推荐算法, 算法结合聚类分析和关联规则挖掘, 能有效实现网页推荐. 实验结果表明, 在保障网页页面推荐覆盖率的条件下, 该方法有较高的精确度、 有效性和实用性.

关键词: 网页推荐, 模糊聚类, 关联规则挖掘, Web日志挖掘

Abstract:

For the traditional Web recommendation based on clustering algorithms has low recommend accuracy, a Web recommended model based on Web log mining was pro
posed, and a main algorithm combined with fuzzy cluster and association rule mining was presented to realize the model. Experiments show the model and the algorithm keep the Web recommending covering rate and also have a higher accuracy.

Key words: Web page recommendation, fuzzy clustering, association rules mining, Web log mining

中图分类号: 

  • TP393.0