Booking.com WSDM WebTour 2021 challenge

Dmitri Goldenberg; Kostia Kofman; Pavel Levin; Sarai Mizrachi; Maayan Kafry; Guy Nadav

Booking.com WSDM WebTour 2021 challenge

Dmitri Goldenberg
, Kostia Kofman
, Pavel Levin
, Sarai Mizrachi
, Maayan Kafry
, Guy Nadav

Research output: Contribution to journal › Conference article › peer-review

5 Scopus citations

Abstract

The ACM WSDM WebTour 2021 Challenge focuses on a multi-destinations trip planning problem, which is a popular scenario in the travel domain. The goal of the challenge is to make the best recommendation of an additional trip destination. To encourage research on this field, Booking.com provided a unique dataset based on millions of real anonymized bookings. More than 800 participants have signed up for the contest. Best performing team achieved Accuracy @ 4 of 0.5939, using a blend of Transformers, GRUs, and feed-forward multi-layer perceptron. Additional leading teams implemented advanced state-of-the-art solutions to tackle the problem.

Original language	English
Pages (from-to)	21-22
Number of pages	2
Journal	CEUR Workshop Proceedings
Volume	2855
State	Published - 1 Jan 2021
Externally published	Yes
Event	2021 Workshop on Web Tourism, WebTour 2021 - Jerusalem, Israel Duration: 12 Mar 2021 → …

Keywords

Challenge
Dataset
Personalization
Recommender Systems
Travel

ASJC Scopus subject areas

General Computer Science

Cite this

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title = "Booking.com WSDM WebTour 2021 challenge",

abstract = "The ACM WSDM WebTour 2021 Challenge focuses on a multi-destinations trip planning problem, which is a popular scenario in the travel domain. The goal of the challenge is to make the best recommendation of an additional trip destination. To encourage research on this field, Booking.com provided a unique dataset based on millions of real anonymized bookings. More than 800 participants have signed up for the contest. Best performing team achieved Accuracy @ 4 of 0.5939, using a blend of Transformers, GRUs, and feed-forward multi-layer perceptron. Additional leading teams implemented advanced state-of-the-art solutions to tackle the problem.",

keywords = "Challenge, Dataset, Personalization, Recommender Systems, Travel",

author = "Dmitri Goldenberg and Kostia Kofman and Pavel Levin and Sarai Mizrachi and Maayan Kafry and Guy Nadav",

note = "Publisher Copyright: Copyright {\textcopyright} 2021 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).; 2021 Workshop on Web Tourism, WebTour 2021 ; Conference date: 12-03-2021",

year = "2021",

month = jan,

day = "1",

language = "English",

volume = "2855",

pages = "21--22",

journal = "CEUR Workshop Proceedings",

issn = "1613-0073",

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TY - JOUR

T1 - Booking.com WSDM WebTour 2021 challenge

AU - Goldenberg, Dmitri

AU - Kofman, Kostia

AU - Levin, Pavel

AU - Mizrachi, Sarai

AU - Kafry, Maayan

AU - Nadav, Guy

PY - 2021/1/1

Y1 - 2021/1/1

N2 - The ACM WSDM WebTour 2021 Challenge focuses on a multi-destinations trip planning problem, which is a popular scenario in the travel domain. The goal of the challenge is to make the best recommendation of an additional trip destination. To encourage research on this field, Booking.com provided a unique dataset based on millions of real anonymized bookings. More than 800 participants have signed up for the contest. Best performing team achieved Accuracy @ 4 of 0.5939, using a blend of Transformers, GRUs, and feed-forward multi-layer perceptron. Additional leading teams implemented advanced state-of-the-art solutions to tackle the problem.

AB - The ACM WSDM WebTour 2021 Challenge focuses on a multi-destinations trip planning problem, which is a popular scenario in the travel domain. The goal of the challenge is to make the best recommendation of an additional trip destination. To encourage research on this field, Booking.com provided a unique dataset based on millions of real anonymized bookings. More than 800 participants have signed up for the contest. Best performing team achieved Accuracy @ 4 of 0.5939, using a blend of Transformers, GRUs, and feed-forward multi-layer perceptron. Additional leading teams implemented advanced state-of-the-art solutions to tackle the problem.

KW - Challenge

KW - Dataset

KW - Personalization

KW - Recommender Systems

KW - Travel

UR - https://www.scopus.com/pages/publications/85105419059

M3 - Conference article

AN - SCOPUS:85105419059

SN - 1613-0073

VL - 2855

SP - 21

EP - 22

JO - CEUR Workshop Proceedings

JF - CEUR Workshop Proceedings

T2 - 2021 Workshop on Web Tourism, WebTour 2021

Y2 - 12 March 2021

ER -

Booking.com WSDM WebTour 2021 challenge

Abstract

Keywords

ASJC Scopus subject areas

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