Air Passenger Image Construction Based on Data Mining Technology

This paper aims to reduce the airline's vacancy rate and make full use of aviation resources to increase the profit by constructing the air passenger image model and forecasting the passenger loss rate based on mining data technology. Firstly, this paper groups the passengers to establish the LRFMC model and obtain the weights of the five indicators by AHP analytic hierarchy process. After weighting the five indicators, the K-means rapid clustering method is used to cluster the passengers. Secondly, construct a logistic regression model to predict the probability of loss. Lastly, based on the conclusions of the established passenger segmentation and loss model, different services and marketing strategies are proposed for different travel groups to attract passengers to take flights and to improve attendance and benefits.