基于二分K均值算法的机场旅客群体划分模型

Airport passenger grouping model based on dichotomic K-means algorithm

为旅客提供个性化服务是机场未来提升服务品质的发展方向,而旅客群体的细分是个性化服务的重要前提。通过提取天津机场安检信息系统旅客数据,分别建立机场旅客主体特征和出行特征划分模型。分析表明,采用二分K均值算法可对机场旅客进行有效划分,聚类结果较为理想。

Providing personalized service for passengers is the developing direction for airport service quality improvement.Passenger data of TBIA security information system is extracted,then the passenger grouping models are respectively built according to their personal characteristics and travelling features.Analysis proves that the dichotomic K-means algorithm can effectively group airport passengers with ideal clustering results.