Design And Accomplishment Of Mobile E-Commerence Recommendation System Based On Multi-model

With the fast development of Internet，E-commerce has become more and morepopular all over the world. Business hence could overcome spatial and temporal barriersand are now capable of serving customers electronically and intelligently. However, theexponentially increasing amount of data and information along with the rapid expansion ofbusiness web sites and information systems make business hard to manage. On the otherhand，it is also difficult for customers to find the products they want. For these reasons，thepersonalized recommendation system arises at the right moment, which providescustomers one-to-one service based on their past behavior and reference from other userswith similar preferences. Many companies nowadays are using this system to retainexisting customers and attract new ones.The article proposes a new multi-models recommendation system’s (MMRS) designand realization based on the current B2C website electronic commerce personalizationrecommendation system’s analysis. The system deals with purchasing history, Wap dataand user’s registration information, uses the associate rule and cluster method,recommending the result in the way of commodities. The plan can give effectiverecommendation and new kinds of commodities to new and old users according to thedifferent information. There is some improvement in recommending calculate and testing itwith some data from a Wap site by my partner, and carrying on a verification to the MMRSsystem, and at the end we can find the improved calculate can receive good effect.