Enhancing Next Destination Prediction: A Novel LSTM Approach Using Real-World Airline Data

This research aims to improve the prediction of travelers’ next destinations by using a novel model architecture based on Long Short-Term Memory (LSTM). This approach is particularly useful in the travel and transportation industry, where accurate predictions can lead to improved customer experiences and targeted marketing. The model was tested on real-world airline data and showed promising results. This study contributes to the advancement of destination prediction methods and has the potential to be applied in various transportation industries.

Publication date: 23 Jan 2024
Project Page: https://arxiv.org/abs/2401.12830v1
Paper: https://arxiv.org/pdf/2401.12830