Web Log-File Data Mining using FID3

• Main Authors: Shu-Yuan Hsu, 許書淵
• Other Authors: Jyh-Yeong Chang
• Format: Others
• Language: en_US
• Published: 2002
• Online Access: http://ndltd.ncl.edu.tw/handle/58495199553820287207

碩士 === 國立交通大學 === 電機與控制工程系 === 90 === The goal of data mining process is knowledge discovery. This thesis applies Fuzzy ID3 to develop a web log-file mining system to analyze the log-file and users’ profile of a B2C website. The web log-file mining system can be divided into three components: data preparation, data engine, and data analysis. The function of data preparation is to convert the log-file from text file to ACCESS database and remove all of the redundance in log-file. The data engine, the kernel of data mining process, is designed to combine the metadata of pages, log-file, and users’ profile. Then the combined database can be the input patterns of fuzzy ID3. The third module of web log-file mining system is data analysis and the data analysis is the final procedure of data mining process. Based on the decision tree constructed by fuzzy ID3, the system will build the fuzzy “IF-THEN” rules and extract information from them. According to these fuzzy rules, the system can realize two applications. One is to provide information about the behavior of the user for web master to maintain and promote the web site. One is to suggest the better browsing path to the user who visits the web site.