Based On Data Mining Technology, Personalized Online Bookstore System Design Studies

With the developing of internet technology rapidly, and with the electronic commerce has become more widely used, more and more data are emerging. The method of data mining was applied in the field of electronic commerce, can help the operators of electronic commerce system get real valuable information form the mass of data, so as to guide them to make more accurate decision. At the same time, it also can offer a series of personalized service. In this thesis, we take example of online bookstore to study and design the personalized online purchasing system based on data mining.Firstly, this thesis analyzes present development situation of data mining technology and electronic commerce and the development of online bookstore programming technology. We establish two data mining analysis models. One model use clustering method which is based on the genetic algorithm (GA) to pretreat customer data, the other model is built to analyze commodity correlation which is based on comprehensive interest. Then we design the online shopping system. The functions of the system include books management subsystem, user operation subsystem and management subsystem of bank. Books management subsystem manages the information of books, orders and customers. User operating system has functions such as user login registered, inquires the books, shopping cart management, order submission, book review and book and so on. Bank management subsystem is in charge of the business with banks. Finally, the thesis use Java as development language and use MySQL as the development databases to achieve the visualization of online bookstore system.The online bookstore system designed in this thesis has more humanized interface and operation more convenient, and more personalized service is also given. It has theoretical significance and practical value.