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

A method for identifying potential customers in the home furnishing industry based on a new bee colony clustering algorithm

A clustering algorithm and customer identification technology, applied in character and pattern recognition, calculation, calculation model, etc., to achieve optimized recognition effect, fast convergence speed, and high recognition accuracy

Inactive Publication Date: 2021-07-20
SHENYANG INST OF AUTOMATION - CHINESE ACAD OF SCI
View PDF8 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] Aiming at the defects exposed by existing calculations when potential customers in the household industry identify such complex clustering problems, the present invention proposes a new bee colony clustering algorithm based on the collaborative foraging behavior of multiple bees in nature Potential customer identification method in home furnishing industry

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
  • A method for identifying potential customers in the home furnishing industry based on a new bee colony clustering algorithm
  • A method for identifying potential customers in the home furnishing industry based on a new bee colony clustering algorithm
  • A method for identifying potential customers in the home furnishing industry based on a new bee colony clustering algorithm

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0035] The present invention will be further described in detail below in conjunction with the examples.

[0036] Such as figure 1 The overall structure of the customer identification process is shown. First, acquire data from the customer database, such as customer basic information, customer preference behavior, etc., to form training and test sample sets. The quality of the acquired data largely affects the quality of the final results; then, in order to achieve Clustering of customers, establishing a potential customer identification model, the trained model needs to be evaluated before it can be used for potential customer identification; finally, according to the constructed potential customer identification model, new visiting customers are identified, potential customers are discovered, and target marketing.

[0037] Step 1: Establish a customer identification model based on the k-means clustering method

[0038] 1.1) Given the number of clusters c;

[0039] 1.2) f...

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

The invention relates to a method for identifying potential customers in the household industry based on a novel bee colony clustering algorithm. The fitness of bees sorts all artificial bees, and selects the first HN positions as food sources; performs clustering operations based on the current positions of artificial bees, and updates the positions of artificial bees: update food sources. The invention is easy to realize, does not rely too much on the selection of parameters, has strong global search ability, fast convergence speed, high recognition accuracy and other advantages, and has a very obvious optimization and recognition effect on the complex clustering problem of potential customer identification in the home furnishing industry .

Description

technical field [0001] The invention relates to a method for identifying potential customers in the home furnishing industry based on a novel bee colony clustering algorithm, which belongs to the field of electronic commerce in the home furnishing industry, and also relates to the fields of swarm intelligence algorithms and clustering algorithms. Background technique [0002] With the advancement of scientific concepts and technologies and the needs of the steady development of the enterprise market, customer assets, as an important intangible asset of an enterprise, have received widespread attention and become one of the key elements to measure the market value of an enterprise. In the "customer-centric" market environment, whether or not a good understanding of customer behavior and the real needs of the market has become the key to determining the competitiveness of enterprises. The success of an enterprise largely depends on whether the enterprise can quickly and accura...

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
Patent Type & Authority Patents(China)
IPC IPC(8): G06K9/62G06N3/00
CPCG06N3/006G06F18/23211
Inventor 朱云龙吕赐兴张浩张丁一
Owner SHENYANG INST OF AUTOMATION - CHINESE ACAD OF SCI
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

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com