Research And Application Of Intelligent E-Commerce Based On Data Warehouse & Mobile Agent

Network and information technology are developed very rapidly. Besides, the third generation is promoted and very popular. All these efforts have made e-commerce and internet trade into every aspect of enterprise management and society. E-commerce offers us a lot of inexhaustible resources based on internet platform. However, too many resources also cause some problems to customers and e-commerce enterprises. For instance, how to offer personalized services, how to identify customer consumption behavior and how to improve competition ability for many small and media e-commerce enterprises. IEC has to face and solve these problems.IEC architecture is established based on database warehouse and mobile agent. On the one hand, database warehouse is built up to execute data mining and form prediction report, which can help enterprise make decision. On the other hand, e-commerce websites can exchange information with other websites by mobile agent so that the website can enhance information abundance and improve completion ability. The innovative results are achieved as following:(1) Refining maximal forward reference mode is proposed and used to acquire user access transaction sequences. These sequences are converted to binary vectors combined with the effective page number. Six rules of ant cluster algorithm are extended to form a new algorithm. These vectors are clustered by the new algorithm, which can realize users cluster and make preparation for personalized services and recommendation.(2) E-commerce transaction volume is predicted as it is very crucial to e-commerce. Data integrity algorithm is presented before forecasting. Extreme learning machine algorithm is proposed to predict the transaction volume and result indicates that the approach has much higher precise.(3) E-commerce customer churn weight is solved by OWA and rough sets. Customer lift cycle and churn prediction model are discussed. As customers losing can make enterprise great losses, OWA and rough sets approaches are presented from the point views of experts and users. The calculation process of churn weight is demonstrated very clearly. The case analysis shows that return and sales services are main reasons for customer churn. Based on results, some measures are proposed.(4) E-commerce alliance architecture is proposed based on mobile agent. Fuzzy SVM is presented to decide whether a website can join the alliance or not. In order to improve the operation of alliance, fuzzy TOPSIS is used to rank the competition of e-commerce.(5) N layers IEC software is developed. It is applied to a commercial website. The result demonstrates the reasonableness of the prototype.