Research And Implementation Of Intelligence E-Commerce Personalization Recommendation Engine Technology

E-commerce Web sites often generate large volumes of data in their daily operations. Analyzing such data involves the discovery of meaningful relationships from access logs stored in Web server. Specially, one of tasks is analyzing user browsing behavior for personal navigation purposes.Based on the B2B DFW e-commerce System for Ox International, Inc. U.S.A, we present an Personalization Recommendation Engine System, drawing heavily upon Web usage mining techniques and Apriori-based Algorithm, making the personalization process automatic, and dynamic. The system architecture separates the offline process of data preparation and Web mining, and the online process of customizing Web pages based on a user's active session.The Recommendation Engine model has been successfully applied to DFW e-commerce System , and it has a good impact on providing Personalization Recommendation pages.