DocumentCode
501203
Title
Research on Classification Management for Branch Post Offices Supplying Insurance Based on TwoStep Cluster
Author
Jinyao, Luo ; Peiji, Shao ; Bin, Luo
Author_Institution
Sch. of Manage. & Econ., Univ. of Electron. Sci. & Technol. of China (UESTC), Chengdu, China
Volume
2
fYear
2009
fDate
15-17 May 2009
Firstpage
75
Lastpage
80
Abstract
Under the adverse conditions occurring in global economy at present, how to boost branch post offices marketing insurance is a difficulty confronted to all the management decision-makers in China Post because supplying insurance is an important operation for them. To break away from the plight, it is a key to evaluate the ability of the branch offices in supplying insurance and data-mining technology is an effective means. In this study, based on analyzing the data of insurance business occurred in the branch post offices, the data which could describe the characteristics of the branch offices were picked up; then the analysis of clustering was completed through using clustering technique which is one of the most important technologies in data mining, moreover, the effect of the feature selection and variables standardizing on the clustering results were analyzed; finally, some advices of management were brought out based on the results of clustering.
Keywords
data mining; decision making; economics; globalisation; insurance data processing; marketing data processing; pattern classification; pattern clustering; postal services; branch post offices; classification management; data mining; decision making; global economy; insurance; marketing; Automatic testing; Clustering methods; Consumer electronics; Data analysis; Data mining; Information technology; Insurance; Marketing management; Packaging; Technology management; TwoStep method; characteristics analysis; clustering; insurance; post operations;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Technology and Applications, 2009. IFITA '09. International Forum on
Conference_Location
Chengdu
Print_ISBN
978-0-7695-3600-2
Type
conf
DOI
10.1109/IFITA.2009.377
Filename
5231281
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