HotelRec: a Novel Very Large-Scale Hotel Recommendation Dataset

Diego Antognini, Boi Faltings


Abstract
Today, recommender systems are an inevitable part of everyone’s daily digital routine and are present on most internet platforms. State-of-the-art deep learning-based models require a large number of data to achieve their best performance. Many datasets fulfilling this criterion have been proposed for multiple domains, such as Amazon products, restaurants, or beers. However, works and datasets in the hotel domain are limited: the largest hotel review dataset is below the million samples. Additionally, the hotel domain suffers from a higher data sparsity than traditional recommendation datasets and therefore, traditional collaborative-filtering approaches cannot be applied to such data. In this paper, we propose HotelRec, a very large-scale hotel recommendation dataset, based on TripAdvisor, containing 50 million reviews. To the best of our knowledge, HotelRec is the largest publicly available dataset in the hotel domain (50M versus 0.9M) and additionally, the largest recommendation dataset in a single domain and with textual reviews (50M versus 22M). We release HotelRec for further research: https://github.com/Diego999/HotelRec.
Anthology ID:
2020.lrec-1.605
Volume:
Proceedings of the Twelfth Language Resources and Evaluation Conference
Month:
May
Year:
2020
Address:
Marseille, France
Editors:
Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
4917–4923
Language:
English
URL:
https://aclanthology.org/2020.lrec-1.605
DOI:
Bibkey:
Cite (ACL):
Diego Antognini and Boi Faltings. 2020. HotelRec: a Novel Very Large-Scale Hotel Recommendation Dataset. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 4917–4923, Marseille, France. European Language Resources Association.
Cite (Informal):
HotelRec: a Novel Very Large-Scale Hotel Recommendation Dataset (Antognini & Faltings, LREC 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.lrec-1.605.pdf
Code
 Diego999/HotelRec
Data
HotelRec