Retail industry dime ticket generating method by employing increment type excavation

A discount coupon and incremental technology, applied in the field of discount coupon generation in the retail industry, can solve problems such as poor integration of algorithms and business decisions, outdated mining methods, and reduced mining efficiency, so as to improve customer satisfaction and loyalty, save Effect of waiting time and improving mining efficiency

Inactive Publication Date: 2009-07-29
ZHEJIANG GONGSHANG UNIVERSITY
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  • Abstract
  • Description
  • Claims
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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] (

Method used

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  • Retail industry dime ticket generating method by employing increment type excavation
  • Retail industry dime ticket generating method by employing increment type excavation
  • Retail industry dime ticket generating method by employing increment type excavation

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Embodiment Construction

[0037] In conjunction with the drawings, the present invention is further described through specific embodiments.

[0038] 1. Establish a retail enterprise product collection, establish a database of discounted products, and establish a database of customer resources.

[0039] 2. Use the MFP algorithm and the CFP algorithm to mine the sales records, obtain the customer purchase patterns in the existing historical database and store them in the database.

[0040] 3. The customer goes shopping, scans and enters the purchased goods at the cash register, and the POS machine sends the shopping list back to the server in the form of a data stream.

[0041] 4. Analyze the latest data flow. For the selected customer, within the selected time period, the combination ABDFG formed by commodity A, commodity B, commodity D, commodity F and commodity G is the largest frequent pattern, and its support count is 123; commodity F, the combined FIP of commodity I and commodity P is also the lar...

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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...

Claims

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Application Information

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IPC IPC(8): G06Q30/00G06F17/30
Inventor 琚春华刘东升周怡孙彬
Owner ZHEJIANG GONGSHANG UNIVERSITY
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