Log summarizing agent for Web access data using data mining techniques

We can get useful information from the WWW (World Wide Web) and the users are increasing every year. The available data is growing explosively, so techniques for analysis and discovery of useful information are important. The information providers and Web manager make an effort to construct an effective Web site. If providers and administrators can determine user browsing patterns from Web access logs, they would be able to use the patterns as one index to construct an effective site. However, it is difficult to extract user browsing patterns manually because the Web access log is huge. Therefore, we adopt a data mining technique to solve this problem and design a log summarizing agent. This agent can automatically extract profitable information from large amounts of Web access logs