Customer relation discovery method based on data vectorization spatial analysis

A data vectorization and spatial analysis technology, applied in the field of data processing and data mining, can solve problems such as analysis differences, achieve strong versatility, and solve the effect of analysis differences

Active Publication Date: 2015-03-25
电信科学技术第十研究所有限公司
View PDF5 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The present invention provides a customer relationship discovery method based on data vectorization spatial analysis to solve the problem of analysis differences caused by clustering analysis methods and classification analysis methods in the prior art under different data set conditions

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
  • Customer relation discovery method based on data vectorization spatial analysis
  • Customer relation discovery method based on data vectorization spatial analysis

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0029] In order to make the object, technical solution and advantages of the present invention clearer, the implementation manner of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0030] An embodiment of the present invention provides a method for discovering customer relationships based on data vectorization spatial analysis, referring to figure 1 As shown, the method includes:

[0031] S1. Vectorize the customer attributes to generate vectorized customer attributes;

[0032] This step specifically includes: vectorizing the qualitative attributes and quantitative attributes of the customers, wherein the qualitative attributes are used to indicate the coordinate points of each customer's location in the geographic space, so The coordinate point is a two-dimensional coordinate point or a three-dimensional coordinate point, and the quantitative attribute is used to indicate a radial line segment centered on the c...

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 provides a customer relation discovery method based on data vectorization spatial analysis, and mainly relates to the technical field of data processing and data mining. The customer relation discovery method based on data vectorization spatial analysis is mainly implemented through vectorization processing of customer attributes. The method has high universality. Through uniform data processing and geographic spatial analysis methods, the problem that in the prior art, a clustering analysis method and a classifying analysis method cause analysis difference under different data sets is effectively solved.

Description

technical field [0001] The invention relates to the technical fields of data processing and data mining, in particular to a method for discovering customer relationships based on data vectorization space analysis. Background technique [0002] Customer relationship discovery is an important link in customer relationship management. Its main purpose is to realize the refined management of customers, so as to realize the customer retention function based on category labels. [0003] At present, the widely used methods of customer relationship discovery mainly include cluster analysis method and classification analysis method. Cluster analysis refers to the analysis process of forming a collection of objects into multiple categories composed of similar objects; classification analysis is a method for identifying which category an individual object belongs to, and the classification process can be based on the data obtained by the cluster analysis method classification model. ...

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 Applications(China)
IPC IPC(8): G06F17/30
CPCG06F16/9537G06F18/23G06F18/24
Inventor 曲彦宾
Owner 电信科学技术第十研究所有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

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

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap