[1]车高营 张磊 张禄旭.基于序列模式的用户浏览行为提取与分析[J].计算机技术与发展,2012,(09):9-12.
 CHE Gao-ying,ZHANG Lei ZHANG Lu-xu.User Browsing Behavior Extraction and Analysis Based on Sequence Pattern[J].,2012,(09):9-12.
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基于序列模式的用户浏览行为提取与分析()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2012年09期
页码:
9-12
栏目:
智能、算法、系统工程
出版日期:
1900-01-01

文章信息/Info

Title:
User Browsing Behavior Extraction and Analysis Based on Sequence Pattern
文章编号:
1673-629X(2012)09-0009-04
作者:
车高营1 张磊2 张禄旭1
[1]上海大学计算机工程与科学学院[2]上海行知学院计算机系
Author(s):
CHE Gao-ying ZHANG Lei ZHANG Lu-xu
[1]School of Computer Engineering and Science, Shanghai University[2]Department of Computer, Shanghai Xingzhi College
关键词:
用户浏览行为分析序列模式层次聚类算法个性化服务浏览模式
Keywords:
user behavior analysis sequential patterns hierarchical clustering algorithm personalized service browsing pattern
分类号:
TP18
文献标志码:
A
摘要:
当今互联网所提供的功能和服务越来越多,Web内容也越来越丰富,移动应用越来越流行。然而,复杂的Web服务应用对用户提出了更高的要求,给用户浏览带来了很多问题,很多时候用户会感到无所适从。文中提出基于用户浏览序列模式的用户行为提取与分析方法。该方法可以分为浏览模式分析和用户聚类两部分。在浏览模式分析时,首先根据用户行为数据得到浏览序列,然后运用序列模式挖掘PrefixSpan算法获取用户习惯的浏览模式,最后把分析获取的用户浏览模式应用到Web浏览中,为不同的用户需求提供个性化的服务。在用户聚类时,运用层次聚类方法按照浏览模式的相似性对用户进行聚类,以分析用户的不同属性(如年龄、职业、学历等)对用户浏览模式的影响。实验结果表明,文中采用的PrefixSpan算法和层次聚类方法在用户浏览模式分析和研究方面具有很好的可行性和有效性
Abstract:
Nowadays, intemet provides more and more application and services, there are more and more contents on Web, and mobile applications develop more and more quickly. Meanwhile, the more sophisticated Web services applications need higher quality of users. Many times some users may feel confused in those Web services. It presents the sequence based on user access patterns for user behavior extraction and analysis methods. The method can be divided into two parts of the browse mode analysis and user clustering. For browse mode analysis, first based on user behavior data get navigation sequence;Then the sequential pattern mining algorithm, so-called PrefixSpan, is used in getting user browsing pattern ; Finally applies user browsing pattern to Web services, and provides personalized services to different users. For user clustering, a hierarchical clustering method is used for splitting user into different categories. The impact of different attributes of user I such as age, occupation, education ) to user clustering is researched. Experimental results show that the PrefixSpan algorithm and hierarchical clustering method used in the browse mode analysis has a good feasibility and validity in this paper

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备注/Memo

备注/Memo:
上海市重点学科建设项目(J50103);上海市教育委员会科研创新项目资助(重点)(11ZZ85);上海市远程教育集团学科研究课题(JF1208)车高营(1983-),男,硕士研究生,研究方向为数据挖掘与用户模型
更新日期/Last Update: 1900-01-01