RWA: A Regression-based Scheme for Flight Price Prediction

Abstract

Flying has become the primary transportation method for long-distance travel. Most of the travelers are intend to purchase the tickets with lowest cost. In practice, many travelers tend to purchase flight tickets as early as possible to avoid possible price hikes. However, this type of purchase behavior does not always lead to the most economical flight tickets.

In our research, we proposed a regression-based scheme, RWA, to improve the accuracy of flight price prediction. Specifically, we first collected a variety of different flight price data sets from publicly-available travel websites. After that, we devised a data splitting method to divide the training data set into two partitions because the price change patterns in these partitions are entirely different. Finally, RWA is applied to each of the partitions to arrive at the accurately-predicted flight price. To verify the effectiveness of RWA, extensive experiments were carried out in our research.