Personalized flight recommendations via paired choice modeling
Jian Cao, Fangzhou Yang, Yuchang Xu, Yudong Tan, Quan-Wu Xiao · 2017
Personalized flight recommendation is useful when a traveler wants to find the most suitable flight ticket efficiently. It is hard to learn latent factors behind personal choices directly from users' preferred flight tickets whose features change over time, which leads to the ineffectiveness of traditional recommendation approaches. Therefore, we propose a personalized flight ticket recommendation approach based on paired choice modeling. In this approach, an optimization problem is formulated to maximize a user's choice utility over flight tickets through a paired-choice analysis of users' historical orders. The experiments conducted on a real world dataset show that our approach outperforms other state-of-the-art methods.