Intelligent Analysis And Application System Of Campus Supermarket Sales Based On Data Mining

With the rapid development of data collection and data storage technology,we have entered the era of large data.Association analysis is one of the most active research directions in data mining.It is used to discover meaningful relationships hidden in large datasets.It has been widely used in the areas of Web mining,document analysis,communication warning analysis,network intrusion detection and bioinformatics.With the rapid development of e-commerce,campus supermarket has brought great competition and pressure to the campus supermarket.How to deeply understand the characteristics of the supermarkets between the campus supermarkets and find out the potential valuable information,Therefore,it is of theoretical and practical value to study the technology of data mining analysis and apply it to the analysis of campus supermarket sales data.Therefore,it is very important to study the data mining technology of campus supermarkets,and to provide a more excellent service for customers is an important problem faced by campus supermarkets.The main work of this paper is as follows:1)Research and analysis of the current development status of data mining technology and its application in supermarket sales data analysis.Based on this,the data warehouse and data mining related technologies are studied and analyzed,OLAP and Apriori algorithm are analyzed in detail,The problem of Apriori algorithm is studied in detail by combining case analysis,and the design of improved Apriori algorithm is put forward,and the correctness and feasibility of the improved algorithm are analyzed by experiment.2)Combining the characteristics of campus supermarket sales data,this paper deeply studies and analyzes the characteristics of OLAP and Apriori algorithm,and proposes a hybrid mining model based on OLAP and Apriori algorithm for the reason of Apriori algorithm consuming in time and space.The efficiency of data mining analysis can be improved effectively and the cost of data mining can be reduced.3)Using the advanced data mining analysis platform-weka,completed the mining model based on OLAP and improved Apriori algorithm,and analyzed the sales data of XXX campus supermarket,and got the correlation between the related products,Which verifies the correctness and reliability of the data mining model design.