基于A-D模型的K-means算法在通话异常客户挖掘中的应用

doi:10.11959/j.issn.1000-0801.2018021

Abstract

Abstract:

In order to make use of massive voice communication records and cluster high-quality clients (telecom fraud clients,advertisers) with various kinds of voice communication abnormalities,a behavioral feature model of abnormal voice communication customers was designed and constructed.Based on the model,a clustering analysis algorithm for customers with abnormal voice communication behavior was proposed.First of all,by analyzing the call records of customers,the characteristics of call behaviors was got,such as the number of calls,call rates,and so on.Then AHP-DEMATEL model was constructed by blending the AHP model and DEMATEL method.Secondly,based on the model,an improved K-means algorithm was proposed to cluster the abnormal clients according to the voice communication records.Finally,the real data was used to verify the analysis.The results show that compared with other similar algorithms,the proposed algorithm improves the performance of multi-type abnormal customer comprehensive clustering analysis and single-type abnormal customer clustering analysis greatly.

Key words: voice communication, abnormal customer mining, behavior characteristics analysis, analytic hierarchy process, decision making trial and evaluation laboratory

CLC Number:

TP391

Jian ZHOU,Yongge SHI,Meibin HE. Application of K-means algorithm based on A-D model in calling abnormal customer mining[J]. Telecommunications Science, 2018, 34(4): 81-89.

Figures/Tables 8

References 20

[1]	刘霞 . 基于电信通话记录的数据挖掘[J]. 计算机与现代化, 2008(6): 36-38.
	LIU X . Application of fuzzy-association rule to telecom data mining[J]. Computer and Modernization, 2008(6): 36-38.
[2]	王家定 . 基于复杂网络理论和通话记录的客户行为异常识别研究[D]. 合肥:中国科学技术大学, 2013.
	WANG J D . Research on customer behavior anomaly recognition based on complex network theory and call logging[D]. Hefei:Uni-versity of Science and Technology of China, 2013.
[3]	石瑛 . 面向电信市场营销的数据挖掘技术研究[D]. 上海:华东师范大学, 2004.
	SHI Y . Research on data mining technology for telecom mar-keting[D]. Shanghai:East China Normal University, 2004.
[4]	赵凯, 蒋朝惠 . 基于 K-means 算法的电信客户行为特征聚类分析[J]. 贵州大学学报:自然科学版, 2015,32(2): 86-90.
	ZHAO K , JIANG C H . Analysis of telecom user behavior fea-tures clustering based on K-means algorithm[J]. Journal of Guizhou University(Natural Science), 2015,32(2): 86-90.
[5]	江哲雅 . 聚类挖掘在电信客户分类中的研究与应用[D]. 上海:上海交通大学, 2013.
	JIANG Z Y . Research and application of clustering mining in telecom customer classification[D]. Shanghai:Shanghai Jiao Tong University, 2013.
[6]	关云鸿 . 改进 K-均值聚类算法在电信客户分类中的应用[J]. 计算机仿真, 2011,28(8): 138-140.
	GUAN Y H . Application of improved K-means algorithm in telecom customer segmentation[J]. Computer Simulation, 2011,28(8): 138-140.
[7]	ZUO G C , ZHOU R H , LI Z Q ,et al. Improved K-means algorithm and its CRM in telecom customer segmentation application[J]. Computer Systems ＆ Applications, 2012,19(11): 155-159.
[8]	FAN G , ZHONG D , YAN F ,et al. A hybrid fuzzy evaluation method for curtain grouting efficiency assessment based on an AHP method extended by D numbers[J]. Expert Systems with Applications, 2016(44): 289-303.
[9]	TZENG G H , CHIANG C H , LI C W . Evaluating intertwined effects in e-learning programs:a novel hybrid MCDM model based on factor analysis and DEMATEL[J]. Expert Systems with Applications, 2007,32(4): 1028-1044.
[10]	原福永, 张晓彩, 罗思标 . 基于信息熵的精确特征赋权K-means聚类算法[J]. 计算机应用, 2011,31(6): 1675-1677.
	YUAN F Y , ZHANG X C , LUO S B . Accurate property weighted K-means clustering algorithm based on information entropy[J]. Journal of Computer Applications, 2011,31(6): 1675-1677.
[11]	瞿英, 路亚静, 刘紫玉 ,等. 基于 AHP-DEMATEL 法的权重计算方法研究[J]. 数学的实践与认识, 2016,46(7): 38-46.
	QU Y , LU Y J , LIU Z Y ,et al. Research on the weight calcula-tion method based on the AHP-DEMATEL method[J]. Mathe-matics in Practice and Theory, 2016,46(7): 38-46.
[12]	丁晓琴, 张德生 . 基于 AHP 和 cRITIc 综合赋权的 K-means算法[J]. 计算机系统应用, 2016,25(7): 182-186.
	DING X Y , ZHANG D S . K-means algorithm based on synthet-ic weighting of AHP and CRITIC[J]. Computer Systems ＆ Ap-plications, 2016,25(7): 182-186.
[13]	王俊凤, 闫文 . 基于AHP-DEMATEL模型的黑龙江省农民专业合作社内部资金互助的影响元素分析[J]. 金融理论与实践, 2016(7): 86-90.
	WANG J F , YAN W . Analysis of the influence of mutual funds between farmer cooperatives in Heilongjiang province based on AHP-DEMATEL model[J]. Financial Theory and Practice, 2016(7): 86-90.
[14]	HUNG S J . Activity-based divergent supply chain planning for competitive advantage in the risky global environment:a DEMATEL-ANP fuzzy goal programming approach[J]. Expert Systems with Applications, 2011,38(8): 9053-9062.
[15]	陈光平, 王文鹏, 黄俊 . 一种改进初始聚类中心选择的K-means算法[J]. 小型微型计算机系统, 2012,33(6): 170-173.
	CHEN G P , WANG W P , HUANG J . Improved initial clustering center selection method for K-means algorithm[J]. Journal of Chinese Computer Systems, 2012,33(6): 170-173.
[16]	熊平, 顾霄 . 基于特征权重最优化的 K-means 聚类算法[J]. 微电子学与计算机, 2014(4): 40-43.
	XIONG P , GU X . K-means clustering algorithm based on fea-ture weight optimization[J]. Microelectronics Computer, 2014(4): 40-43.
[17]	刘春, 邹海锋, 向勇 . 大数据环境下电信数据服务能力开放研究[J]. 电信科学, 2014,30(3): 156-161.
	LIU C , ZOU H F , XIANG Y . Research on telecom data service open ability under the environment of big data[J]. Telecommu-nications Science, 2014,30(3): 156-161.
[18]	韩晶, 张智江, 王健全 ,等. 面向统一运营的电信运营商大数据战略[J]. 电信科学, 2014,30(11): 154-158.
	HAN J , ZHANG Z J , WANG J Q ,et al. The uni-fied-operation-oriented big data strategy for telecom operators[J]. Telecommunications Science, 2014,30(11): 154-158.
[19]	曹旭, 曹瑞彤 . 基于大数据分析的网络异常检测方法[J]. 电信科学, 2014,30(6): 152-156.
	CAO X , CAO R T . Network anomaly prediction method based on big data[J]. Telecommunications Science, 2014,30(6): 152-156.
[20]	谷红勋, 杨珂 . 基于大数据的移动用户行为分析系统与应用案例[J]. 电信科学, 2016,32(3): 139-146.
	GU H X , YANG K . Mobile user behavior analysis system and applications based on big data[J]. Telecommunications Science, 2016,32(3): 139-146.

Metrics

Recommended 0

No Suggested Reading articles found!

	c₁	c₂	c₃	c₄	c₅	c₆	c₇
z	0	0.555	0.555	0.555	0.101	0.101	0.228
g	0.228	0	0.555	0.555	0.101	0.101	0.555
q	0.150	0.916	0	0.370	0	0	0

	c₁	c₂	c₃	c₄	c₅	c₆	c₇
y	0.088	0.215	0.178	0.233	0.044	0.044	0.195
z	0	0.264	0.264	0.264	0.048	0.048	0.109
g	0.109	0	0.264	0.264	0.048	0.048	0.264
q	0.104	0.637	0	0.257	0	0	0

	c₁	c₂	c₃	c₄	c₅	c₆	c₇
c₁	0.325	0.793	0.735	0.735	0.583	0.583	0.701
c₂	0.570	0.712	0.992	0.992	0.829	0.829	0.869
c₃	0.584	1.117	1.207	1.430	1.197	1.197	1.193
c₄	0.584	1.117	1.430	1.207	1.197	1.197	1.193
c₅	0.028	0.548	0.861	0.861	0.691	0.913	0.675
c₆	0.028	0.548	0.861	0.861	0.913	0.691	0.675
c₇	0.550	1.015	0.888	1.343	1.343	1.231	0.975

	c₁	c₂	c₃	c₄	c₅	c₆	c₇
R_i	3.193	5.852	7.432	7.432	6.643	6.643	6.283
D_i	4.458	5.796	7.927	7.927	4.84	4.84	7.689
R_i+D_i	7.651	11.378	15.359	15.359	11.483	11.483	13.973

	c₁	c₂	c₃	c₄	c₅	c₆	c₇
W_y	0.051	0.185	0.208	0.271	0.038	0.038	0.207
W_z	0	0.218	0.295	0.295	0.040	0.040	0.110
W_g	0.06	0	0.295	0.295	0.040	0.040	0.268
W_q	0.066	0.604	0	0.329	0	0	0

Application of K-means algorithm based on A-D model in calling abnormal customer mining

RichHTML

PDF下载

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 8

References 20

Related Articles 7

Metrics

Recommended 0

K	召回率			准确率			F值
K	本文算法	K-means	参考文献[7]算法	本文算法	K-means	参考文献[7]算法	本文算法	K-means	参考文献[7]算法
4	0.68	0.56	0.71	0.92	0.91	0.66	0.78	0.69	0.68
5	0.92	0.88	0.83	0.95	0.80	0.83	0.93	0.83	0.83
6	0.91	0.81	0.87	0.91	0.71	0.90	0.91	0.75	0.88
7	0.82	0.82	0.87	0.93	0.77	0.93	0.87	0.79	0.89

[1]	Qizhu ZHONG. Research and application of media streams based on entropy and FAHP [J]. Telecommunications Science, 2020, 36(4): 145-153.
[2]	Yang LIU. Planning algorithm of small cell deployment scheme [J]. Telecommunications Science, 2017, 33(11): 195-200.
[3]	Rui Zhang,Jing Hu,Weiwei Xia. Network Selection Algorithm Based on Stable Matching Game in Vehicular Heterogeneous Network [J]. Telecommunications Science, 2015, 31(9): 51-59.
[4]	Cun Yang,Jihong Zhao,Shuyuan Zhao. Research on Network Selection Algorithm Based on User Preference in Heterogeneous System [J]. Telecommunications Science, 2014, 30(6): 67-72.
[5]	Chen Xiaoming,Wang Huiqiang,Lv Hongwu and Zhu Qiang. Evaluation Method for Future Network Quality of Service Based on Multi-Layer Federation [J]. Telecommunications Science, 2012, 28(11): 52-59.
[6]	Fenghua Li,Ce Zhang,Zhongmin Wang,Yi Li. Design of the Firmware for Stackable VoIP Card [J]. Telecommunications Science, 2009, 25(4): 62-67.
[7]	Li Fenghua,Zhang Ce,Wang Zhongmin and Li Yi. Design of the Firmware for Stackable VoIP Card [J]. Telecommunications Science, 2009, 25(3): 62-67.