DocumentCode :
496824
Title :
Application of Fuzzy-C-Means Algorithm Based on Rough Set in Client Subdivision Research
Author :
Wang, Jing ; Fang, Niu Gai ; Sun, Qingyu
Author_Institution :
Dept. of the Libr., Hebei Univ. of Eng., Handan, China
Volume :
1
fYear :
2009
fDate :
18-19 July 2009
Firstpage :
28
Lastpage :
31
Abstract :
In an increasingly competitive market, the management of client relationship is becoming a key point for a enterprise to get a success in the competition, client subdivision is a foundation for the enterprise to make a precise marketing strategy and a successful management of client group, based on the development of data mining technology, a fuzzy-C-means(FCM) algorithm model is founded to do the client subdivision in this paper, Selecting the rough set (RS) to make a reduction to the redundancy attributes of the sample, thus reducing the dimensions of the sample input space, at a certain extent improved the accuracy and the classify effect of this algorithm, through analyses the clustering results, we provide a quantitative basis for the enterprise in the proceeding of making a marketing strategy, enhanced the pertinency and efficiency of the enterprise marketing activities.
Keywords :
data mining; fuzzy set theory; marketing data processing; rough set theory; client subdivision research; data mining; fuzzy-C-means algorithm; marketing strategy; rough set theory; Algorithm design and analysis; Clustering algorithms; Conference management; Engineering management; Fuzzy set theory; Information analysis; Marketing management; Research and development management; Resource management; Technology management; client subdivision; fuzzy-c-means algorithm; rough set;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Processing, 2009. APCIP 2009. Asia-Pacific Conference on
Conference_Location :
Shenzhen
Print_ISBN :
978-0-7695-3699-6
Type :
conf
DOI :
10.1109/APCIP.2009.15
Filename :
5196987
Link To Document :
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