Design And Implementation Of Mobile Mall System Based On Association Rules Algorithm

With the proliferation of mobile users,and the wide application of 4G network and WIFI technology,as a new business model,mobile e-commerce is meeting more and more consumers who are from different regions,different ages and different demands,and it is popular with so many businesses and users,nowadays,it has been widely used in various types of business activities.Mobile mall attracts a large number of users with the large number of products,the variety of categories,the convenience of search,the cheapness of commodities and the lack of time and space constraints and other advantages,which leads the online shopping by mobile devices to become the preferred way for most people.However,owing to the increase of mobile mall system users and commodity type,users can't find desired goods quickly and accurately.Aiming at the above problem,this paper designs a mobile mall system based on association rule algorithm.This system adopts MVC(Model View Controller)model,and uses JavaScript,PHP and Ajax technology to achieve asynchronous interaction based on the development platform which use PHP5.0 and MySQL.This system can recommend related products for users,help users position product information quickly and accurately,and improve the efficiency of online shopping.The main work of this paper is as follows:1.This thesis summarizes data mining and association rule mining technology,simultaneously introduces its basic principle,the realization process,and the summary analysis,and finally points out research direction of association rules algorithm.2.This thesis has a overall analysis of the classical algorithm-Apriori of association rules mining,and proposes an improved association rule mining algorithm based on Apriori by analyzing the limitation of Apriori.Improved algorithm does not need to produce the candidate item sets,only scans transaction database to store transaction data with frequent item sets matrix form and calculate its reduction,occupies less storage space,and deals with transaction data services quickly.Based on the theoretical analysis,the algorithm based on Apriori improved association rule mining algorithm is proved to have higher mining efficiency while ensuring time complexity and space complexity.3.This thesis introduces demand analysis,architecture design and function module design of mobile mall system.The main function modules are realized,and function modules include purchase of goods,goods return customer service,customer information management,integration activities and commodity recommendation.This thesis focuses on the research of commodity recommendation module,and uses the improved association rule algorithm to find out the association rules among the commodities and recommend products for users through the collection of the information of users' order transaction.