Web Mining: An Overview

interactions with Web sites. The motive of mining is to find users’ access models automatically and quickly from the vast Web log data, such as frequent access paths, frequent access page groups and user clustering. Through web usage mining, the server log, registration information and other relative information left by user provide foundation for decision making of organizations. This article provides a survey and analysis of current Web usage mining systems and technologies. There are generally three tasks in Web Usage Mining: Preprocessing, Pattern analysis and Knowledge discovery. Preprocessing cleans log file of server by removing log entries such as error or failure and repeated request for the same URL from the same host etc... The main task of Pattern analysis is to filter uninteresting information and to visualize and interpret the interesting pattern to users. The statistics collected from the log file can help to discover the knowledge. This knowledge collected can be used to take decision on various factors like Excellent, Medium, Weak users and Excellent, Medium and Weak web pages based on hit counts of the web page in the web site. The design of the Web usage mining is a main research area in Web mining focused on learning about Web users and their website is restructured based on user’s behavior or hit counts which provides quick response to the web users, saves memory space of servers and thus reducing HTTP requests and bandwidth utilization. This paper addresses challenges in three phases of Web Usage mining along with Web Structure Mining.This paper also discusses an application of WUM, an online Recommender System that dynamically generates links to pages that have not yet been visited by a user and might be of his potential interest. Differently from the recommender systems proposed so far, ONLINE MINER does not make use of any off-line component, and is able to manageWeb sites made up of pages dynamically generated