Modeling Multi-Destination Trips with Sketch-Based Model
원문 초록
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.
함께 살펴볼 논문
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Differentiable Nonlinear Model Predictive Control
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Graph World Model
Compress Any Segment Anything Model (SAM)
Hierarchical Intent-guided Optimization with Pluggable LLM-Driven Semantics for Session-based Recommendation
토론
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