Apply Web Mining Techniques to Analyze the Navigation Behavior of Visitors - Using Online Content Site as Example
Date Issued
2005
Date
2005
Author(s)
Su, Chun-pin
DOI
zh-TW
Abstract
According to the survey report, issued by TWNIC Jan. 2005, Internet popularity had grown to 13,800,000 users, about 4,630,000 home families, approaching 65% of whole families in Taiwan. Therefore, the Internet not only is a powerful media, but also become an important channel to enterprises. All enterprises are eager to find out a useful way to synergize such a powerful channel. They have been trying to analyze the visiting log of the web, and mine the behavior of customers who had contacted the enterprise through the Internet, willing to collect more customer information and provide more personalized services to customers. However, in practicality, there are some difficulties encountered. The First is the web logs are distributed information, which are separated on several servers, and need to be integrated and do lots of processing. Secondary, one of the difficulties is how to extract the key features from the huge logs, and how to solve the scalability issues. The third problem is how to find the suitable mining tools to discover the implicit knowledge from bunch of irrelevant raw data.
Our research proposes a novel framework, which integrates most useful public domain resources and some self-developed tools, provides powerful analyzing tools to overcome such difficulties. This thesis also illustrates a novel algorithm to visualize click-stream mining result, named “Click-map”. This presentation is able to assist the web master to discover users’ navigation behaviors from the click path analysis more easily.
For examining the availability of the framework and analysis methods, we use online web logs for the period of one month as examples. The logs came from an online content search services site, with 1.26GB data size and over 66 million records, recorded from March to April in 2005. The results proofed our framework to be useful and effective.
Subjects
網路探勘
網頁使用探勘
網誌分析
點閱行為分析
瀏灠行為分析
最大前向參考路徑
點閱路徑地圖
瀏灠路徑
資料探勘
Web Usage Mining
User Navigation Behavior Analysis
Click-stream Analysis
Web Log Mining
Path Traversal Pattern Mining
Maximum Forward Reference
Webhouse
Click-map
Web Mining
Type
other
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