Attention-based neural re-ranking approach for next city in trip recommendations

• URL: http://arxiv.org/abs/2103.12475v1
• Date: Tue, 23 Mar 2021 11:56:40 GMT
• Title: Attention-based neural re-ranking approach for next city in trip recommendations
• Authors: Aleksandr Petrov, Yuriy Makarov
• Abstract summary: This paper describes an approach to solving the next destination city recommendation problem for a travel reservation system. We propose a two stages approach: an approach for candidates selection and an attention neural network model for candidates re-ranking.
• Score: 77.34726150561087
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This paper describes an approach to solving the next destination city recommendation problem for a travel reservation system. We propose a two stages approach: a heuristic approach for candidates selection and an attention neural network model for candidates re-ranking. Our method was inspired by listwise learning-to-rank methods and recent developments in natural language processing and the transformer architecture in particular. We used this approach to solve the Booking.com recommendations challenge Our team achieved 5th place on the challenge using this method, with 0.555 accuracy@4 value on the closed part of the dataset.

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