Proceedings
Copyright © 2024 for the individual papers by the papers’ authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). This volume is published and copyrighted by its editors. The copyright for papers appearing in these proceedings belongs to the papers’ authors.
This volume is published by Julia Neidhardt, Tsvi Kuflik, Amit Livne & Markus Zanker.
Proceedings of the Workshop on Recommenders in Tourism
This volume contains the contributions of the Workshop on Recommenders in Tourism (RecTour), organized in
conjunction with the 18th ACM Conference on Recommender System
Providing timely and relevant information about destinations, accommodations, and services is particularly challenging in this context. Moreover, many tourism information providers are small or medium-sized enterprises (SMEs) that lack the resources to implement even basic recommendation systems. The absence of standardized data formats further complicates system development. Additionally, tourism products are often co-produced during the interaction between the consumer and provider, making the context of recommendations critically important.
The rapid advancement of information and communication technologies (ICT), especially the web, has revolutionized tourism, reducing travelers’ reliance on traditional travel agents. Studies show that travelers now actively use ICT to craft personalized vacation packages, often seeking free, real-time information on-site instead of relying on potentially outdated and costly visitor guides. However, the abundance of online information can lead to information overload, making recommender systems a valuable tool for streamlining the decision-making process. Despite their potential, designing effective recommender systems for the tourism sector remains a formidable task due to its complexity. This workshop brings together researchers and practitioners from diverse fields - such as tourism, recommender systems, user modeling, human-computer interaction, mobile and ubiquitous technologies, artificial intelligence, and web information systems - who are engaged in the tourism recommendation domain. The event aims to foster discussion on innovative solutions to the specific challenges faced in this area and to advance the state-of-the-art in tourism recommender systems. Additionally, it seeks to explore practical applications of these technologies from the perspectives of individual users, user groups, service providers, and other stakeholders, including destination management organizations and government agencies.
Finally, RecTour 2024 aims to build on the community engagement and dialogues initiated in previous workshops, continuing to strengthen collaboration and innovation within this dynamic field.
• Julia Neidhardt, Christian Doppler Laboratory for Recommender Systems, TU Wien, Austria • Tsvi Kuflik, Information Systems Department, The University of Haifa, Israel • Amit Livne, Booking.com, Tel Aviv, Israel • Markus Zanker, Free University of Bozen/Bolzano, Italy and University of Klagenfurt, Austria Program Committee • • • • • •
Derek Bridge, University College Cork, Ireland Dietmar Jannach, AAU Klagenfurt, Austria Jan Krasnodebski, Expedia Group, Switzerland Antonio Moreno, Universitat Rovira i Virgili, Spain Francesco Ricci, Free University of Bozen/Bolzano, Italy Wolfgang Wörndl, TU Munich, Germany
Acknowledgement
Keynote Presentation: “Expanding the Boundaries: Recommender Systems and the
This keynote presentation explores the transformative potential of recommender systems within the tourism industry, while also examining the broader technological and sustainable trends emerging in adjacent fields. Moving beyond the traditional tasks and vocabulary known in the RecSys community, this presentation will showcase techniques and methods in use in other research areas (such as IoT, Operational Research, or Data Mining) that could be useful for the attendees of this workshop. Through case studies and real-world examples, we illustrate the synergies, challenges, and potential impact such technologies may bring to the community.
Alejandro Bellogín is Associate Professor at Universidad Autónoma de Madrid (UAM), Spain. Previously, he was associated to the Centrum Wiskunde & Informatica under a postdoctoral Marie Curie research grant. Dr. Bellogín has worked in several areas of user modeling and personalization, including recommender systems, evaluation, and reproducibility, where he has published over 80 conference and journal papers, while being involved as program or organization committees in venues related to these areas, such as RecSys, WWW, and UMAP, among others. In the last years, his focus was around the topics of fairness and tourism, where he leads national and industry projects aiming at transferring these research problems and solutions to the society.
The RecTour 2024 Challenge, organized by Booking.com as part of RecTour 2024, focused on improving the ranking of user reviews for accommodations, a crucial factor in user decision-making. While traditional methods rank reviews based on scores, recency, or helpfulness votes, the challenge addressed the limitations of these approaches, including presentation bias.
The task required participants to match users and accommodations to relevant review IDs to enable personalized review rankings based on user preferences and accommodation features. A unique training dataset of 1.6 million reviews from real anonymized bookings was provided. Participants leveraged this data to develop models that ranked reviews considering user-accommodation characteristics.
The competition included training, validation, and test datasets. The performance was evaluated using the MRR@10 metric, with submissions including predictions of the top 10 reviews for each user-accommodation pair. Participants created negative labels from the Matches file and ensured compliance with dataset requirements, such as informative reviews and unique matches.
The challenge began on June 20, 2024, with the validation and test datasets released in August. Final leaderboard submissions were due at the beginning of September 2024. Top teams were invited to submit papers on their solutions for the workshop.
09:00 - 09:30: Opening and Welcome 09:30 - 10:30: Keynote Presentation by Alejandro Bellogín 10:30 - 11:15: Coffee Break • 12:45 - 14:30: Lunch Break Research Papers • TRACE: Transformer-based User Representations from Attributed Clickstream Event Sequences Authors: William Black, Alex Manlove, Jack Pennington, Andrea Marchini, Ercument Ilhan, and Vilda Markeviciute………………………………………………………………………………………………...1-10 • Multi-funnel Recommender System for Cold Item Boosting
Authors: Ahmed Khaili, Kostia Kofman, Edgar Cano, Adva Hadrian, and Andrew Mende………...……11-22 • Structured Entity Extraction from Travel Videos Using Vision-Language Models
Author: Kevin Dela Rosa………………………………………………………………………….………23-30 • Lifecycle of Promotional Campaigns in the Online Travel Industry
Authors: Carlos Herrero, Amit Livne, Itsik Adiv, Hugo Manuel Proença, Felipe Moraes, Javier Albert, and Dima Goldenberg…………………………………………………………………………………………31-38 • SMARTIE: Smart Museum for All Using a Range of Technology for Inclusive Experience
Authors: Alexandra Danial-Saad, Yael Avni, Julia Sheidin, and Tsvi Kuflik…………………………….39-48 • A Multimodal Dataset and Benchmark for Tourism Review Generation
Authors: Hiromasa Yamanishi, Ling Xiao, and Toshihiko Yamasaki…………………………………….49-67 • A Roadmap for Privacy Preserving Tourist Recommendation Systems
Authors: Alan Wecker, Noa Tuval, Alain Hertz, Mohammad Mahamid, and Tsvi Kuflik…….…………68-73 Industry Paper • Journey to Centralizing Destination Recommendations
Authors: Maria Prosviryakova, Gaurav Misra, Sebastien Le Digabel, and Rodrigo Villatoro…………....74-81