Analysis of Users Behaviour in Structured E-Commerce Websites

Abstract

Online shopping is becoming more and more common in our daily lives. Understanding users’ interests and behavior is essential in order to adapt e-commerce websites to customers’ requirements. The information about users’ behavior is stored in the web server logs. Nowadays, the growth of World Wide Web has exceeded a lot with more expectations. The internet is growing day by day, so online users are also rising. The interesting information for knowledge of extracting from such huge data demands for new logic and the new method. Every user spends their most of the time on the internet and their behaviour is different from one and another. Web usage mining is the category of web mining that helps in automatically discovering user access pattern. Web usage mining is leading research area in Web Mining concerned about the web user’s behaviour. In this paper emphasizes is given on the user behaviours using web server log file prediction using web server log record, click streams record and user information. Users using web pages, frequently visited hyperlinks, frequently accessed web pages, links are stored in web server log files. A Web log along with the individuality of the user captures their browsing behaviour on a website and discussing regarding the behavior from analysis of different algorithms and different methods