Web Usage Mining is the process of automatic extraction of user navigation patterns from the Web Log files. Search Engines and e-Commerce websites collect a lot of clickstream data and leverage this technique to provide their users with personalized content. Using traditional web usage mining techniques in an enhanced manner valuable patterns and hidden knowledge can be discovered. Most of the techniques require the use of algorithms like k-Nearest Neighbors and Decision Trees. This paper intends to evaluate the Compact Prediction Tree algorithm based on their accuracy and variation for the next web page prediction purpose.
Software And Hardware
• Hardware: Processor: i3 ,i5 RAM: 4GB Hard disk: 16 GB • Software: operating System : Windws2000/XP/7/8/10 Anaconda,jupyter,spyder,flask Frontend :-python Backend:- MYSQL