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ACTA AERONAUTICAET ASTRONAUTICA SINICA ›› 2018, Vol. 39 ›› Issue (2): 321608-321608.doi: 10.7527/S1000-6893.2017.21608

• Electronics and Electrical Engineering and Control • Previous Articles     Next Articles

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).

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

CLC Number: