Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Unattended store shelf layout optimization based on electronic label data analysis

An electronic label and data analysis technology, applied in the fields of electrical digital data processing, special data processing applications, electromagnetic radiation induction, etc., can solve the problems of small support and increase the difficulty of setting support

Inactive Publication Date: 2018-01-05
ZHEJIANG GONGSHANG UNIVERSITY
View PDF1 Cites 4 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although this method is simple and clear, it has a fatal flaw: how to set the minimum support
The user's unknown to the database increases the difficulty of setting support

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Unattended store shelf layout optimization based on electronic label data analysis
  • Unattended store shelf layout optimization based on electronic label data analysis
  • Unattended store shelf layout optimization based on electronic label data analysis

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0053] The present invention will be further described in detail in conjunction with the accompanying drawings and specific embodiments.

[0054] The unattended store shelf layout optimization method based on electronic tag data analysis proposed by the present invention comprises the following steps:

[0055] Step 1. Commodity real-time data collection: electronic tags and RFID technology are installed in unattended stores, and electronic price tags are used to collect sales data and sales prices of each product, as well as the shelf position of the product, and the data stored in the electronic tag system Import SQL database;

[0056] Step 2. Data preprocessing: delete messy data in the original data through data cleaning operations, correct wrong data, remove blank data, noise and irrelevant data, etc.; such as deleting return information, connecting multiple tables for query, and classifying products;

[0057] Step 3. Mining frequent itemsets: using Top-K frequent itemset...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

A shelf layout optimization method for commodity data analysis of an unattended store specifically relates to knowledge in the fields such as electronic label commodity real-time data acquisition, association mining algorithms and frequent item set mining. The method is particularly applicable to analysis and processing of real-time data of commodities of an unattended store. An electronic label is used to collect commodity data; an association analysis algorithm is adopted, and performance of the algorithm is improved as much as possible from the perspective of optimizing a frequent item set;and by use of an improved degree-of-interest algorithm, an association among commodities is accurately found, so as to instruct optimization of a shelf layout of the unattended store. On the basis ofexisting commodity data analysis, the present invention provides a Top-K frequent item set mining algorithm based on a node set; and a POC-Tree data structure is used to compress transmitted data, sothat the limitation that the algorithm scans the database for multiple times is avoided, and the difficulty that the degree of support is hard to be set during the association rule mining process issuccessfully solved by means of better performance.

Description

technical field [0001] The invention includes a shelf layout optimization method for product data analysis in unattended stores, and specifically involves knowledge in the fields of electronic label product real-time data collection, association mining algorithms, frequent item set mining, and the like. It is especially suitable for analyzing and processing real-time data of products in unattended stores, and collects product data with the help of electronic tags, uses correlation analysis algorithms to improve algorithm performance as much as possible from the perspective of optimizing frequent collection items, and adopts improved interest degree algorithm, so as to accurately Find out the relationship between products to guide the optimization of shelf layout in unattended stores. technical background [0002] With the explosive growth of information, in the era of big data, data is becoming a key asset in the enterprise to provide important decision-making basis in the p...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
IPC IPC(8): G06F17/30G06K7/10G06K17/00
Inventor 肖亮汪澍李晓敏袁霄
Owner ZHEJIANG GONGSHANG UNIVERSITY
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products