Journal of Computer Applications ›› 2014, Vol. 34 ›› Issue (6): 1807-1811.DOI: 10.11772/j.issn.1001-9081.2014.06.1807
Previous Articles Next Articles
Received:
2013-11-22
Revised:
2014-01-03
Online:
2014-07-02
Published:
2014-06-01
Contact:
XUE Yun
林勤1,薛云2
通讯作者:
薛云
作者简介:
基金资助:
国家自然科学基金资助项目;广州市科技计划项目;广东医学院面上基金资助项目
CLC Number:
LIN Qin XUE Yun. Application of biclustering algorithm in high-value telecommunication customer segmentation[J]. Journal of Computer Applications, 2014, 34(6): 1807-1811.
林勤 薛云. 双聚类算法在电信高价值客户细分的应用[J]. 计算机应用, 2014, 34(6): 1807-1811.
Add to citation manager EndNote|Ris|BibTeX
URL: https://www.joca.cn/EN/10.11772/j.issn.1001-9081.2014.06.1807
[1]ZEITHAML V A, RUST R T, LEMON K N. The customer pyramid: creating and serving profitable customers [J]. California Management Review, 2001,43(4):118-142.
[2]JACKSON B B. Build customer relationships that last [J]. Harvard Business Review, 1985,63(10):120-128.
[3]BERGER P D, NASR N I. Customer lifetime value: marketing models and applications [J]. Journal of Interactive Marketing, 1998,12(1):17-30.
[4]CHEN M. Research of customer retention and lifetime value [D]. Xi'an: Xi'an Jiaotong University, 2001.(陈明亮.客户保持与生命周期研究 [D].西安:西安交通大学,2001.)
[5]QI J. Research of enterprise customer value [D]. Xi'an: Xi'an Jiaotong University, 2002.(齐佳音.企业客户价值研究[D].西安:西安交通大学,2002.)
[6]QU Z, ZHENG Y, LYU T. Realizing customer behavious analysis based on clustering [J]. Journal of Northeast Normal University: Natural Science, 2006,38(2):19-21.(曲昭伟,郑岩,吕廷杰.基于聚类实现客户行为分析[J].东北师大学报:自然科学版,2006,38(2):19-21.)
[7]ZHAO M, NI Z, LIU B. Application research of K-means clustering and naive Bayesian algorithm in business intelligence [J]. Computer Technology and Development, 2010,20(4):179-182.(赵敏, 倪志伟, 刘斌.K-means与朴素贝叶斯在商务智能中的应用[J].计算机技术与发展,2010,20(4):179-182.)
[8]ZHENG G, ZHANG B, GUO P, et al. Analysis of clustering algorithm in behavior mode of customers in China telecom [J]. Journal of Chongqing University: Natural Science, 2006,29(4):119-121.(郑国荣,张邦礼,郭鹏,等.聚类分析在电信消费模式中的应用[J].重庆大学学报:自然科学版,2006,29(4):119-121.)
[9]SHABALIN A A, WEIGMAN V J, PEROU C M, et al. Finding large average submatrices in high dimensional data [J]. The Annals of Applied Stastistics, 2009,3(3):985-1012.
[10]CHENG Y, CHURCH G M. Biclustering of expression data [EB/OL]. [2013-07-03]. ftp://samba.ad.sdsc.edu/pub/sdsc/biology/ISMB00/157.pdf.
[11]DHILLON I S. Co-clustering documents and words using bipartite spectral graph partitioning [C]// KDD 2001: Proceedings of the 7th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York: ACM Press, 2001:269-274.
[12]BANERJEE A, DHILLON L, GHOSH J, et al. A generalized maximum entropy approach to Bregman co-clustering and matrix approximations [C]// KDD 2004: Proceedings of the 10th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York: ACM Press, 2004:509-514.
[13]SU X, KHOSHGOFTAAR T M. A survey of collaborative filtering techniques [J]. Advances in Artificial Intelligence, 2009,2009(4):421-445.ns [J]. Journal of Cybernetica, 1974,4(1):95-104.
[15]CALINSKI T, HARABASZ J. A dendrite method for cluster analysis [J]. Communication in Stastistics, 1974,3(1):1-27. |
Viewed | ||||||
Full text |
|
|||||
Abstract |
|
|||||