Customer Classification of Discrete Data Concerning Customer Assets Based on Data Mining

被引：2

作者：

Zuo Lei ^{[1
]}

Guo Junfeng ^{[1
]}

机构：

[1] Harbin Finance Univ, Harbin 150030, Heilongjiang, Peoples R China

来源：

2019 INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION, BIG DATA & SMART CITY (ICITBS) | 2019年

关键词：

Discrete data; Customer Classification; Customer Assets; Data Mining;

D O I：

10.1109/ICITBS.2019.00093

中图分类号：

TN [电子技术、通信技术];

学科分类号：

0809 ;

摘要：

selecting useful information under the background of big data can help enterprises to classify customers more accurately. Outlier data includes important customer information. In order to study customer classification problem based on customer asset outlier data, a customer classification model based on outlier data analysis concerning customer asset is constructed successfully. The model is based on Variables in 4 dimensions including transaction frequency, types of products or services traded, transaction amount and client age. And using clustering before classification to divide twenty-five types of outlier customer data into four categories and corresponding marketing strategies also are put forward according to different classification of outlier customer data of a company.

引用

页码：352 / 355

页数：4