Design And Implementation Of Fresh Food Supermarket Business System Based On Data Analysis

With the development of society and the continuous improvement of people's living standards,fresh agricultural products as an indispensable food and nutritional sources on the table,people's demand for it is also growing.Chain fresh food supermarket as a new mode of operation,because of its unified management,fresh agricultural products,the safety and quality of more secure,therefore more and more welcomed by consumers.However,with the continuous development and expansion of fresh food supermarket business,fresh food supermarket business information system has developed slowly.Enterprise's existing supermarket business system often does not take into account the uniqueness of fresh agricultural products,lacks the coverage of the whole business and not considering the special requirements,The chain fresh food supermarket enterprises don't make the best use of these data which accumulated in the business process with data analysis and data mining technology.This paper designed and developed a fresh food supermarket business system which is more suitable for a enterprise in Changchun City,applied the cluster analysis and association rules in data mining to the sales data of enterprise.In order to help enterprises to develop a more reasonable management and marketing strategy we combined the analysis of sales data with data mining technology and business system together.The main work is divided into two parts: The first part is the implementation of basic function module in the fresh food supermarket business system.The system used the popular Java language and open source SSH framework to complete the development of each module in the system.The basic business module of the system mainly includes user management,acceptance of sales data,warehouse-in inspection,dispatch goods,store transfer,goods reported loss,procurement plans,store orders,merchandise management,goods in transit,return sales processing,etc.Fresh food supermarket operations in each link can be traceable,completed the data sharing and the entire business informatization.The merchandise in transit information management was developed with the open source OpenLayers which built a lightweight Web GIS module based on JavaScript.In addition,taking into account the urgent needs of the procurement staff for the mobile office,completed the design and implementation of the procurement management mobile App which could help buyers carry out procurement work better;The second part of the work is the design and implementation of the chain fresh food supermarket sales data analysis.Because in the course of business of fresh food supermarket will accumulate a large amount of data and sales data for each store is different,so we can use the store sales data with cluster analysis.However,after researching the fuzzy C-means clustering algorithm in cluster analysis,found that the algorithm need to specify the cluster number before cluster defects,then introducing the Mixed F distribution in statistics to solve this problem.This method proposed in this paper could overcome the shortcomings of FCM which needs a specific initial parameters and apply the improved algorithm to the analysis of the sales characteristics of the fresh food supermarket.Then designed and implemented the basket analysis module,every customer's goods trading data can be called shopping basket data.Data mining technology in the association rules are more applicable to the fresh food supermarket customer shopping basket transaction data analysis,so the module use Apriori association rules mining algorithm to analyze the customer's shopping basket data.Through the experimental results,the two modules can find potential information in large amounts of data enterprises accumulated in the process of operation,provide help to the actual operation and management for enterprise.