Abstract: Potential high-value passengers can not be effectively discovered by airways due to the limited historical booking records of passengers. Aiming at this problem, a probabilistic model for discovering potential high-value passengers based on trip purposes mining is proposed. Firstly, we present a probabilistic model based on statistics to measure the value of passengers. Then, trip purposes are introduced into the model to discover potential airline demands of each passenger and to optimize passenger potential value calculation. Therefore, potential high-value passengers can be discovered through the trip purposes mining. Experiments show that the proposed model can identify the potential high-value passengers more accurately than the traditional passenger value evaluation methods based on the passengers' cumulative number of flight times, passengers' cumulative mileage and recency frequency monetry model.

Key words: civil aviation passengers, probabilistic model, trip purposes, potential value, potential airline demand