Research on recommender technology in E-commerce recommendation system

Abstract

E-commerce companies compete with each other nowadays, and one solution to winning the competition is to get knowledge about customers' consuming preferences so as to establish better adequate personalized services to satisfy the customers. On this surrounding, to make E-commerce system actively recommend products to users according to their interests, the E-commerce recommendation system is arrived and gradually develops which supported by the agent technologies derived from Artificial Intelligence. In the paper, concepts and functions of E-commerce recommender systems are briefly introduced. The algorithms using in recommendation systems are comparing with each other, and several main filtering algorithms are described. Advantages and disadvantages of these above mentioned technical recommendations were provided. At last, point out several open research problems and directions in the E-commerce recommendation methods.