Unlock instant, AI-driven research and patent intelligence for your innovation.

User loyalty classification method

A loyalty and user technology, applied in special data processing applications, structured data retrieval, marketing, etc., can solve the problem that the k value is difficult to estimate the classification accuracy, so as to solve the impact of operation efficiency and classification accuracy, enhance data Basics, the effect of ensuring accuracy

Inactive Publication Date: 2021-03-02
SICHUAN CHANGHONG ELECTRIC CO LTD
View PDF3 Cites 1 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In addition, the Canopy algorithm is used for rough clustering of user data, and then the K-means algorithm is used for precise clustering of users, which solves the impact of the K-means algorithm on the operating efficiency and classification accuracy of the K-means algorithm because it is difficult to estimate and sensitive to outliers.

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
  • User loyalty classification method
  • User loyalty classification method
  • User loyalty classification method

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0040] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be described in detail below. Apparently, the described embodiments are only some of the embodiments of the present invention, but not all of them. Based on the embodiments of the present invention, all other implementations obtained by persons of ordinary skill in the art without making creative efforts fall within the protection scope of the present invention.

[0041] In either embodiment, if figure 1As shown, a kind of user loyalty classification method of the present invention, based on user's static geographical location information, user behavior data, combines Canopy algorithm and K-means algorithm to carry out loyalty classification to user, in comprehensive consideration affects user loyalty evaluation On the basis of all factors, the accurate classification of enterprise user loyalty is realized. The user in ...

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 discloses a user loyalty classification method, which adds user static information and geographic position information into user data for user loyalty evaluation through a GIS geocodingtechnology, so that the data basis for user loyalty evaluation is enhanced. The Canopy algorithm is adopted to carry out coarse clustering on the user data, then the K-means algorithm is utilized to carry out accurate clustering on the users, and accurate classification of the loyalty of the enterprise users is realized on the basis of comprehensively considering all factors influencing loyalty evaluation of the users.

Description

technical field [0001] The invention relates to the technical field of enterprise data mining, in particular to a method for classifying user loyalty. Background technique [0002] As the seller's market gradually turns into a buyer's market, users have replaced enterprises as the leader of business activities, and users have become the decisive factor for the success or failure of enterprises. But different users have different meanings to the enterprise. The famous "80 / 20 rule" has already revealed that only 20% of the users (basically all loyal users of the enterprise) can really bring profits to the enterprise. While attracting new users, it is especially necessary to pay attention to cultivating the loyalty of existing users. [0003] The existing technologies for evaluating enterprise user loyalty all collect user behavior data first, and then use classification algorithms to classify user loyalty. In this process, the existing technology ignores the impact of user s...

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): G06Q30/02G06F16/29G06K9/62
CPCG06Q30/0201G06F16/29G06F18/23213
Inventor 杨钱钱唐军谢禹
Owner SICHUAN CHANGHONG ELECTRIC CO LTD
Features
  • R&D
  • Intellectual Property
  • Life Sciences
  • Materials
  • Tech Scout
Why Patsnap Eureka
  • Unparalleled Data Quality
  • Higher Quality Content
  • 60% Fewer Hallucinations
Social media
Patsnap Eureka Blog
Learn More

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

© 2025 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com