Retail industry dime ticket generating method by employing increment type excavation

Abstract

The invention provides a cash voucher generation method adopting incremental mining in the retail trade, which mainly comprises a series of processes including using a card, excavating data stream, accessing of knowledge base and printing cash vouchers. Each customer has a membership card which is for free. When the customer uses the card for shopping, a computer automatically checks the shopping mode of the customer, if the shopping mode meets certain conditions, a cash voucher for the customer is automatically printed after a shopping receipt is printed. Concrete steps are as follows: 1. a commodity inventory of retail enterprises, discount commodity database and customer resource database are established; 2. the collection of daily database information and the excavation of long-term data are carried out; 3. commodities bought are scanned and input and each POS machine sends shopping lists of customers to a data excavating tool for generating customer consumption records after data preprocessing; and 4. cash vouchers of conventional consumables or commodities predicted to be bought are printed and discount information is stored in the customer resource database simultaneously.

Description

technical field [0001] The invention relates to a method for generating discount coupons in the retail industry. Background technique [0002] In the retail industry, the application of computer and information technology has become more and more popular. The POS system and the management information system (MIS) record a large amount of customer transaction data, and are updating with a huge amount of data every day. However, traditional commercial data mining has the following defects: [0003] (1) The mining method used is relatively old. The traditional data mining method is based on the information of the historical database. Today, with the explosive growth of information, the amount of database scanning data is increasing day by day, the mining task is aggravated, and the mining efficiency is decreasing day by day. [0004] (2) Using data stream mining can improve the efficiency of analysis, but the existing methods have defects in accuracy. [0005] (3) Even if mor...

AI Technical Summary

Problems solved by technology

[0003] (1) The mining method used is relatively old. The traditional data mining method is based on the information of the historical database. Today, with the explosive growth of information, the amount of database scanning data is increasing day by day, the mining task is aggravated, and the mining efficiency is decreasing day by day.

[0004] (2) Using data stream mining can improve the efficiency of analysis, but existing methods have defects in accuracy

[0005] (3) Even if more advanced commercial data streams are used for mining, an effective algorithm has not been found to dynamically integrate marketing behaviors with data streams

[0006] The present invention aims to solve the defects of low efficiency of commercial decision-making in the retail industry, insufficient accuracy and poor combination of algorithms and commercial decision-making, and at the same time dynamically collect data to increase the accuracy of data

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