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Publications

Our publications in Data Science, Machine Learning and Experimentation

Christina Katsimerou

A/B/n testing with control in the presence of subpopulations

Published in NeurIPS 2021 by: Yoan Russac, Christina Katsimerou, Dennis Bohle, Olivier Cappé, Aurélien Garivier and Wouter M. Koolen

Kees Jan de Vries

Machine Learning for Fraud Detection in E-Commerce: A Research Agenda

Published in: (2021) Machine Learning for Fraud Detection in E-Commerce: A Research Agenda. In: Wang G., Ciptadi A., Ahmadzadeh A. (eds) Deployable Machine Learning for Security Defense. MLHat 2021…

Booking.com @ RecSys 2021

Booking.com’s publications at the 15th ACM conference on Recommender Systems

Mining the Stars: Learning Quality Ratings with User-facing Explanations for Vacation Rentals

Published in the 14th ACM International Conference on Web Search and Data Mining WSDM 2021

Dima Goldenberg

Personalization in Practice

Methods and Applications — a WSDM ’21 Tutorial

Dima Goldenberg

Uplift Modeling

From Causal Inference to Personalization — Tutorial

Dima Goldenberg

Booking.com WSDM WebTour 2021 Data Challenge

Booking.com sponsors the ACM WSDM WebTour 2021 Challenge…

Booking.com Data Science

A fundamental problem of hypothesis testing with finite inventory in e-commerce

Published in Applied Stochastic Models in Business and Industry by Dennis Bohle, Alexander Marynych, Matthias Meiners

Booking.com Data Science

Recommending Accommodation Filters with Online Learning

Presented in the Workshop on Online Recommender Systems and User Modeling ORSUM ACM RecSys 2020 by Lucas Bernardi, Pablo Estevez, Matias Eidis and Eqbal Osama

Booking.com Data Science

Beyond algorithms: Ranking at scale at Booking.com

Published in Recsys 2020, ComplexRec by Themis Mavridis, Soraya Hausl, Andrew Mende, Roberto Pagano

Paper: http://www.toinebogers.com/workshops/complexrec2020/Mavridis.pdf

Free Lunch! Retrospective Uplift Modeling for Dynamic Promotions Recommendation within ROI Constraints

Published in Recsys 2020, by Dima Goldenberg, Javier Albert, Pablo Estevez and Lucas Bernardi.

Booking.com Data Science

Efficient Image Gallery Representations at Scale Through Multi-Task Learning

Published in SIGIR ‘20 by Benjamin Gutelman, Pavel Levin

Paper: https://dl.acm.org/doi/abs/10.1145/3397271.3401433

Booking.com Data Science

Cross-lingual intent classification in a low resource industrial setting

Published in EMNLP 2019 by Talaat Khalil, Kornel Kielczewski, George Chouliaras, Amina Keldibek and Maarten Versteegh

Booking.com Data Science

Combining Context Features in Sequence-Aware Recommender Systems

presented in RecSys 2019 Late-breaking Results, 16th-20th September 2019, Copenhagen, Denmark by Sarai Mizrachi and Pavel Levin

Booking.com Data Science

150 Successful Machine Learning Models: 6 Lessons Learned at Booking.com

Published in KDD 2019 by Lucas Bernardi, Themis Mavridis and Pablo Estevez

Paper: https://dl.acm.org/doi/10.1145/3292500.3330744

Booking.com Data Science

Mediation Analysis in Online Experiments at Booking.com: Disentangling Direct and Indirect Effects

Published in CODE 2018 by Tolga Oztan, Zoé van Havre, Caio Gomes, Lukas Vermeer

Booking.com Data Science

Learning to Match

Published in WSDM 2018 by Themis Mavridis, Pablo Estevez, Lucas Bernardi

Paper: https://arxiv.org/pdf/1802.03102.pdf

Booking.com is a virtual two-sided marketplace where guests and accommodation providers are the two distinct stakeholders. They…

Booking.com Data Science

Toward a full-scale neural machine translation in production: the Booking.com use case

Published in MT Summit XVI by Pavel Levin, Nishikant Dhanuka, Talaat Khalil, Fedor Kovalev, Maxim Khalilov

Booking.com Data Science

Machine Translation at Booking.com: Journey and Lessons Learned

Published in EAMT 2017 by Pavel Levin, Nishikant Dhanuka, Maxim Khalilov

Paper: https://ufal.mff.cuni.cz/eamt2017/user-project-product-papers/papers/user/EAMT2017_paper_86.pdf

Booking.com Data Science

Democratizing online controlled experiments at Booking.com

Published in CODE 2017 by Raphael Lopez Kaufman, Jegar Pitchforth, Lukas Vermeer

Paper: https://arxiv.org/abs/1710.08217

Booking.com Data Science

Leaky Abstraction In Online Experimentation Platforms: A Conceptual Framework To Categorize Common Challenge

Published in CODE 2015 by Timo Kluck, Lukas Vermeer

Booking.com Data Science

Where to Go on Your Next Trip? Optimizing Travel Destinations Based on User Preferences

Published in SIGIR 2015 by Julia Kiseleva, Melanie Mueller, Lucas Bernardi, Chad Davis, Ivan Kovacek, Mats Einarsen, Jaap Kamps, Alexander Tuzhilin and Djoerd Hiemstra

Booking.com Data Science

The Continuous Cold Start Problem in e-Commerce Recommender Systems

Published in RecSys 2015 by Lucas Bernardi, Jaap Kamps, Julia Kiseleva and Melanie Mueller

Paper: https://arxiv.org/pdf/1508.01177.pdf

Booking.com Data Science

User Engagement through Topic Modelling in Travel

Published in KDD 2014 by Athanasios Noulas and Mats Einarsen

Paper: http://www.ueo-workshop.com/wp-content/uploads/2014/04/noulasKDD2014.pdf

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