A customer segmentation model based on affinity propagation algorithm and improved genetic k-means algorithm

doi:10.1007/978-3-030-00828-4_32

CORC > 西安光学精密机械研究所 > 中国科学院西安光学精密机械研究所 > 光学影像学习与分析中心

	A customer segmentation model based on affinity propagation algorithm and improved genetic k-means algorithm
	Zhang, Meiyang 1; Zhang, Zili 1,2; Qiu, Shi 3
	2018
会议日期	2018-10-19
会议地点	Nanning, China
卷号	538
DOI	10.1007/978-3-030-00828-4_32
页码	321-327
英文摘要	Customer Relationship Management System (CRM) has accumulated massive customer transaction data. Effective customer segmentation by analyzing transaction data can contribute to marketing strategy designing. However, the state-of-the-art researches are defective such as the uncertain number of clusters and the low accuracy. In this paper, a novel customer segmentation model, AP-GKAs, is proposed. First, factor analysis extracts customer feature based on multi-indicator RFM model. Then, affinity propagation (AP) determines the number of customer clusters. Finally, the improved genetic K-means algorithm (GKAs) is used to increase clustering accuracy. The experimental results showed that the AP-GKAs has higher segmentation performance in comparison to other typical methods. © IFIP International Federation for Information Processing 2018.
产权排序	3
会议录	Intelligent Information Processing IX - 10th IFIP TC 12 International Conference, IIP 2018, Proceedings
会议录出版者	Springer New York LLC
语种	英语
ISSN号	18684238
ISBN号	9783030008277
内容类型	会议论文
源URL	[http://ir.opt.ac.cn/handle/181661/30696]
专题	西安光学精密机械研究所_光学影像学习与分析中心
通讯作者	Zhang, Zili
作者单位	1.College of Computer and Information Science, Southwest University, Chongqing; 400715, China; 2.School of Information Technology, Deakin University, Locked Bag 20000, Geelong; VIC; 3220, Australia; 3.Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi’an; 710119, China
推荐引用方式 GB/T 7714	Zhang, Meiyang,Zhang, Zili,Qiu, Shi. A customer segmentation model based on affinity propagation algorithm and improved genetic k-means algorithm[C]. 见:. Nanning, China. 2018-10-19.