DocumentCode
3267328
Title
Application of Grey Relational Clustering and Data Mining in Data Flow of E-Commerce
Author
Zhiming, Qu ; Xiaoying, Liang
Author_Institution
Sch. of Civil Eng., Hebei Univ. of Eng., Handan, China
Volume
1
fYear
2009
fDate
6-7 June 2009
Firstpage
237
Lastpage
240
Abstract
The data mining of E-commerce is to extract implicit, valuable business and understandable information from vast information to guide future business activities. As an important branch of data mining, grey relational clustering has become a hot research spot in the field of data mining because its form is simple, easy to be interpreted and understood, and it describes the important data relationship effectively from large databases in recent years. Through grey relational clustering, it is concluded that the intrinsic link among goods, goods sale and customer, is found out, which is of very important guiding significance for personalized commodity recommendation, enterprise market positioning and the corresponding invoicing strategy in e-commerce.
Keywords
data mining; electronic commerce; grey systems; pattern clustering; statistical analysis; data flow; data mining; e-commerce; enterprise market; grey relational clustering; personalized commodity recommendation; statistical analysis; Artificial intelligence; Civil engineering; Companies; Computer networks; Data engineering; Data mining; Decision making; Delta modulation; Electronic commerce; Internet; E-commerce; data flow; data mining; grey relational clustering;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Natural Computing, 2009. CINC '09. International Conference on
Conference_Location
Wuhan
Print_ISBN
978-0-7695-3645-3
Type
conf
DOI
10.1109/CINC.2009.57
Filename
5231161
Link To Document