The development and evaluation of configurable web usage analyzer / Nasrul Azli Ahmad

Learning Web users’ preferences and adapting the Web information structure to the users’ behaviors can improve the effectiveness of the particular websites. In addition, automatic knowledge extraction from the Web server log files, page tags, network packets and cookies can be useful for identifying such reading patterns and infer user profiles in order to design the website suited for different group of users. Therefore we develop a Web Usage Analyzer System in order to extract the useful implicit and previously unknown patterns from the usage of the website. In our study we analyzed an online course using web usage mining techniques by analyzing users’ behavior in terms of site usage, involvement of the most active users from their navigational activities and the number of visits throughout the semester of the course. By using this system, lecturer manage to analyze students’ behavior in terms of site usage such as last date accessed, login name, time and visited page. Lecturer can also investigate the trends of the website in terms of popularity by identifying the most visited page. In conclusion, the Web Usage Analyzer System provides great features to the lecturer to investigate and analyze the users’ behaviors, activities and their performances.