Hybrid Model for Preprocessing and Clustering of Web Server Log

With increased rate in the usage of the World Wide Web (www) is growing both in its complexity and the volume of traffic of web site, it has become very important to analyze this web traffic and the usage of the web site by the users. Web usage mining is a main research area in web mining focused on learning about web users and their interaction with web sites. The information like server log, browser cookies and other relative information can be used to find user’s access models automatically and quickly from the web log data, such as most frequent access parts, least recent access page group and user cluster[1][2]. In this paper we are analyzing the system by implementing the major recommendation approaches and preprocessing of log files stored in web server by applying clustering algorithm. Based on that, we are extracting valuable information along with the behavior of interested users and web designer to enhance better foundation for decision making of an organization and better service to the customer and web users Keyword-: Clustering approach, Knowledge set, Preprocessing and, Server log file, Web usage mining