| 基于兴趣度的Web用户访问模式分析 |
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| 引用本文： | 吕佳. 基于兴趣度的Web用户访问模式分析[J]. 计算机工程与设计, 2007, 28(10): 2403-2404,2407 |
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| 作者姓名： | 吕佳 |
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| 作者单位： | 重庆师范大学,数学与计算机科学学院,重庆,400047 |
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| 基金项目： | 重庆市教委资助项目 , 重庆师范大学校科研和教改项目 |
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| 摘 要： | Web日志隐含了用户访问Web行为的动因和规律,如何有效地从中挖掘出用户访问模式是Web日志挖掘的重要研究内容.构造了User_ID-URL矩阵,矩阵元素为用户访问页面的兴趣度.应用经典的模糊C-均值聚类算法进行用户访问模式分析,通过在真实数据集上的实验,结果表明引入了用户兴趣度的日志挖掘算法是行之有效的.
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| 关 键 词： | Web日志 用户兴趣度 用户访问模式 模糊C-均值 聚类分析 |
| 文章编号： | 1000-7024（2007）10-2403-02 |
| 修稿时间： | 2006-04-06 |
Web user access patterns clustering based on interest degree |
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| L Jia. Web user access patterns clustering based on interest degree[J]. Computer Engineering and Design, 2007, 28(10): 2403-2404,2407 |
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| Authors: | L Jia |
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| Affiliation: | College of Mathematics and Computer Science, Chongqing Normal University, Chongqing 400047, China |
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| Abstract: | Web logs contain motivation and rules of user access web actions, how to effectively mine user access patterns from web logs is an important research content in web log mining. User_ID-URL matrix is constructed, and matrix element uses user access interest degree. Classical fuzzy C-means clustering algorithm is applied to analyze user access patterns. The experiments used to real data set show web log mining algorithm adding user interest degree is effective and feasible. |
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| Keywords: | web log user interest degree user access patterns fuzzy C-means clustering analysis |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
