航空学报 > 2018, Vol. 39 Issue (2): 321608-321608   doi: 10.7527/S1000-6893.2017.21608

一种融合个体属性与社交关系的民航旅客价值度量方法

丁建立1,2, 刘晓庆1, 王家亮1,2   

  1. 1. 中国民航大学 计算机科学与技术学院, 天津 300300;
    2. 中国民航大学 天津市智能信号与图像处理重点实验室, 天津 300300
  • 收稿日期:2017-07-14 修回日期:2017-11-03 出版日期:2018-02-15 发布日期:2017-11-03
  • 通讯作者: 刘晓庆,E-mail:154552879@qq.com E-mail:344043534@qq.com
  • 基金资助:
    民航局创新重大专项(MHRD20150107);中国民航大学天津市智能信号与图像处理重点实验室开放基金(2015ASP02);中国民航大学中央高校基金项目(3122016A001,3122015C020)

A method for measuring civil aviation passenger value by combining individual attributes and social relations

DING Jianli1,2, LIU Xiaoqing1, WANG Jialiang1,2   

  1. 1. College of Computer Science and Technology, Civil Aviation University of China, Tianjin 300300, China;
    2. Tianjin Key Laboratory for Advanced Signal and Image Processing, Civil Aviation University of China, Tianjin 300300, China
  • Received:2017-07-14 Revised:2017-11-03 Online:2018-02-15 Published:2017-11-03
  • Supported by:
    Major Projects of Civil Aviation Technology Innovation Funds of China (MHRD20150107); Tianjin Key Lab Open Fund for Advanced Signal and Image Processing of Civil Aviation University of China (2015ASP02); Fundamental Research Funds for the Central Universities of Civil Aviation University of China (3122016A001, 3122015C020).

摘要: 针对目前民航旅客关系网络中旅客关系类别单一、旅客价值计算滞后、旅客潜在价值计算没有考虑旅客之间的相互影响,使得一些具有极大消费潜力的旅客因为目前乘机次数较少而被航空公司忽略的现状,提出了一种融合个体属性与社交关系的民航旅客价值度量方法,采用RFMc模型计算旅客个体价值,并采用多关系评价(MRE)模型分析旅客关系,然后通过改进的PageRank算法设计实现融合旅客个体价值和社交关系的民航旅客价值排序(CAPV-Rank)算法,实现旅客价值度量、旅客价值预测和潜在高价值旅客挖掘。实验结果表明:设计实现的CAPV-Rank算法可通过调整权重因子实现多种模式下的旅客价值计算,满足各种业务需求,并能实现旅客价值预测、潜在高价值旅客挖掘,旨在为民航旅客价值度量和预测提供灵活、高效的解决方案。

关键词: 社交关系, 个体价值, PageRank, 旅客价值度量, 潜在高价值旅客

Abstract: In the civil aviation passenger network, the type of relations among passengers is single, and calculation of passenger value is lagging behind. The calculation method for the passenger potential value does not take into account the interaction between passengers, making the passengers who seldom travel by plane but have great potential for consumption in the future ignored by the airlines. A method for measuring the civil aviation passenger value by combining individual attributes and social relations is proposed. First, the RFMc model is used to calculate the individual value of passengers, and the MRE model is adopted to analyse the relationship of passengers. PageRank is then improved to implement the proposed Civil Aviation Passenger Value Rank (CAPV-Rank) algorithm, which merges the individual value and social relationship of the passengers. The CAPV-Rank algorithm is designed to realize the passenger value measurement, the passenger value forecast and potential high value passenger mining. Experimental results show that the CAPV-Rank algorithm can implement the passenger value measurement in various modes by adjusting the weighting factor, and can satisfy various business requirements. The algorithm can also realize the passenger value forecast and potential high-value passenger mining, providing a flexible and efficient solution for the measurement and forecast of civil aviation passenger value.

Key words: social relations, individual value, PageRank, passenger value measurement, potential high value passenger

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