Design And Implementation Of The E-book Based On Data Mining Bureau

With the rapid development of internet technology, and the popularization ofe-commerce mode,there are more and more business data utilized in the internet. Toapply data mining technology to the e-commerce system, contributes to getting the realvaluable information behind the large amount of data, therefore the manager ofe-commerce can make more accurate decision, and understand the users’individualdemand.In this thesis, we introduce the current situation of e-commerce and data miningtechnology, analyze the online bookstore’s functional requirements, establish two maindata mining and analyzing model: one model is custom data pretreatment by clusteringmethod based on genetic algorithm, and the other is commodity correlation based oncomprehensive interest. What’s more, we design and implement the online bookstoresystem, which can analyze and mine the data in the online platform. The primaryfunctions of this system include member management, books management, ordermanagement and data analysis, etc. The key is mutual connection of main part in theeach subsystem, which consists of members, books, orders. The system not onlyprovides the registration and login, bibliographic query, shopping cart management,order submission, book review and reservation for users, but also traces and analyzesthe members’personalized data by combine with the ideas and methods of data miningfully.By means of testing, running, completing repeatedly, the function and performanceof this system meet demand of customers, and take the method of high quality service inonline bookstore. More importantly, the data analysis subsystem with theoreticalsignificance and practical value can provide more effective information for themanagers when they make important decision.The online bookstore system designed in this thesis has more humanized interfaceand operation more convenient, and more personalized service is also given. It hastheoretical significance and practical value.