摘要
针对民航客户行为数据的复杂性,运用数据挖掘中的DBSCAN聚类技术,结合核映射机理,提出一种基于核的DBSCAN算法,用于实现民航客户的细分。实验结果表明,该方法能突出客户之间的行为特征差异,降低聚类结果的混乱性,且其聚类纯度比原DBSCAN算法约提升30%。
This paper proposes a kernel-based DBSCAN algorithm which is aiming at the complexity of the civil aviation passenger behavior.The algorithm uses the DBSCAN clustering technology,combines with the nuclear mapping mechanism,and realizes civil aviation customer segmentation.Experimental results show that the method can highlight the differences between samples,and also can reduce the confusion of the clustering results and the cluster purity is improved by nearly 30%.
出处
《计算机工程》
CAS
CSCD
2012年第10期70-73,共4页
Computer Engineering
基金
国家"863"计划基金资助重点项目"基于服务架构的民航公众信息服务平台"(2006AA12A106)
中国民用航空局科技基金资助项目(MHRD201130)
关键词
客户关系管理
数据挖掘
核DBSCAN算法
民航客户细分
Customer Relationship Management（CRM）
data mining
kernel DBSCAN algorithm
civil aviation customer segmentation
