Modeling Multi-Destination Trips with Sketch-Based Model (Best Paper Award)

Abstract

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.com 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.

Publication
ACM WSDM Workshop on Web Tourism
Michal Daniluk
Michal Daniluk
Research Scientist

My research interests include graph representation learning, recommendation systems, behavioral user representations, NLP.