Classification technique to understanding user behavior using web mining

Abstract

Nowadays web is a very growing field, all companies and venders are doing their business over the internet under web based systems, According to Strong desire from users and customers to deal with these systems, companies become with a huge number of information about them, from this point there is a need to regulate this growing data in every moment to maintain the relationship between these institutions and their customers to know everything about them, their behaviors, and what they prefer? Web mining is referred to the application of data mining methodologies, techniques, and models to the variety of data forms, structures, and usage patterns that comprise the World Wide Web. As the subtitle indicates, we are interested in uncovering patterns and trends in the content, structure, and use of the web. The research problem is in three key points: The presence of large number of users in the websites, the presence of huge amount of data about users, and the need of the web master and site administration to technology enables them to make a quick decision. The main objectives of this research are to perform web usage mining process, specifically to extract knowledge from (www.interactivegt.com) website server log, to analyze user's behavior and interests, improving the web site from the user‟s point of view, and determining errors and corrupted links to fix them. Web usage mining methodology is our target method to extract knowledge from log files that contain user and customer transactions, queries and registered data. Web usage mining information may be used in many applications in our case we used this results in how to understand user behavior in (www. interactivegt.com) web site what their preferences and interests.