DocumentCode
2086625
Title
Improved K-Means cluster algorithm in telecommunications enterprises customer segmentation
Author
Zhao, Jinghua ; Zhang, Wenbo ; Liu, Yanwei
Author_Institution
Comput. Coll., Jilin Normal Univ., Siping, China
fYear
2010
fDate
17-19 Dec. 2010
Firstpage
167
Lastpage
169
Abstract
According to the actual requirements of telecommunications enterprises customer segmentation, in this paper an improved K-Means algorithm was introduced. The algorithm was used to initialize cluster center in the cluster analysis phase of Data Mining technology. The experimental results proved that the novel algorithm has greater improvement than the original one in efficiency and accuracy. The results applying the novel method to telecommunications enterprises customer segmentation showed that the segmentation results obtained can be used as the data basis in differentiated services for customers and have positive significance for product design and phone packages recommendation.
Keywords
customer services; data mining; pattern clustering; product design; telecommunication computing; telecommunication industry; K-means cluster algorithm; cluster analysis; customer segmentation; data mining; phone packages recommendation; product design; telecommunications enterprises; Algorithm design and analysis; Analytical models; Business; Clustering algorithms; Computational modeling; Data mining; Telecommunications; Customer Segmentation; Data Mining; K-Means Cluster Algorithm; Telecommunications Enterprise;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Theory and Information Security (ICITIS), 2010 IEEE International Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4244-6942-0
Type
conf
DOI
10.1109/ICITIS.2010.5688749
Filename
5688749
Link To Document