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Papers

Modeling Multi-Destination Trips with Sketch-Based Model

2021-02-22 · Michał Daniluk, Barbara Rychalska, Konrad Gołuchowski, Jacek Dąbrowski

The recently proposed EMDE (Efficient Manifold Density Estimator) model achieves state of-the-art results in session-based recommendation. In this work we explore its application to Booking Data Challenge competition. The aim of the challenge is to make the best recommendation for the next destination of a user trip, based on dataset with millions of real anonymized accommodation reservations. We achieve 2nd place in this competition. First, we use Cleora - our graph embedding method - to represent cities as a directed graph and learn their vector representation. Next, we apply EMDE to predict the next user destination based on previously visited cities and some features associated with each trip. We release the source code at: https://github.com/Synerise/booking-challenge.

📄 PDF Abstract BibTeX arXiv:2102.11252

Code (1)

Synerise/booking-challenge 공식 구현 pytorch

Tasks

Graph EmbeddingmodelSession-Based Recommendations

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