Dynamic Recommendation System Using Web Usage Mining for E-commerce Users

Abstract

E-commerce organizations are growing exponentially with time in terms of both business and data. Many organizations rely on these websites to attract new customers and retain the existing ones. In order to achieve this goal web log files can be used that records customer's access patterns. Using traditional web usage mining techniques in an enhanced manner valuable patterns and hidden knowledge can be discovered. This paper focuses on providing real time dynamic recommendation to all the visitors of the website irrespective of been registered or unregistered. Action based rational recommendation technique is proposed that makes use of lexical patterns to generate item recommendation. Effectiveness of the proposed system is evaluated by collecting real time E commerce data and comparing the system with user based and product based techniques. Results prove that the proposed system yield good quality accuracy and minimizes limitations of traditional recommendation system.