Web usage mining based on WAN users' behaviors

被引：0

作者：

Yan, Hao ^{[1
]}

Zhang, Bo ^{[1
]}

Zhang, Yibo ^{[1
]}

Liu, Fang ^{[1
]}

Lei, Zhenming ^{[1
]}

机构：

[1] Beijing Univ Posts & Telecommun, Sch Informat & Commun Engn, Beijing 100088, Peoples R China

来源：

2010 6TH INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS NETWORKING AND MOBILE COMPUTING (WICOM) | 2010年

关键词：

Web usage mining; usage pattern; clustering; targeting and recommending applications;

D O I：

暂无

中图分类号：

TP3 [计算技术、计算机技术];

学科分类号：

0812 ;

摘要：

Web mining focuses on extracting useful information from large volumes of Web data. Web usage mining (WUM) is one of important application which applies Web mining techniques to discovery usage patterns from Web accessing data. Meanwhile clustering performs a key role in distinguishing different kinds of usage patterns from raw data. Considering usage features of activities, information scope and preference, we propose a two-step K-means clustering algorithm to search user groups in realistic data collected from WAN. In the paper, some useful practical conclusions are also presented to facilitate design of targeting and recommending applications.

引用

页数：5

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