Study on Retail Customer Classification Based on Support Vector Machine

Author

Qian, Yangfeng ; Ju, Chunhua

Author_Institution

Emerson CT, Shenzhen

fYear

2009

fDate

23-24 May 2009

Firstpage

1

Lastpage

5

Abstract

In this paper, the authors propose application of data mining method of support vector machine to large scale retail enterprises and establish a consumer behavior model SVMCC based on support vector machine. The model adopts the mapping mechanism and uncertain reasoning of cloud processing to distinctly express the relations among multi-attributes which affect the result of classification. This model can efficiently deal with the problem of high dimensional-linear-inseparableness. Finally, the authors present a specific case of application.

Keywords

data mining; inference mechanisms; learning (artificial intelligence); pattern classification; retail data processing; support vector machines; cloud processing; consumer behavior model; data mining method; dimensional-linear-inseparableness; large scale retail enterprise; machine learning method; retail customer classification; support vector machine; uncertain reasoning; Clouds; Concrete; Consumer behavior; Data mining; Large-scale systems; Machine learning; Machine learning algorithms; Statistics; Support vector machine classification; Support vector machines;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Systems and Applications, 2009. ISA 2009. International Workshop on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-3893-8

Electronic_ISBN

978-1-4244-3894-5

Type

conf

DOI

10.1109/IWISA.2009.5073141

Filename

5073141