In 2019, the Recommender Systems Challenge [17] dealt for the first time with a real-world task from the area of e-tourism, namely the recommendation of hotels in booking sessions. In this context, we present the release of a new dataset that we believe is vitally important for recommendation systems research in the area of hotel search, from both academic and industry perspectives. In this article, we describe the qualitative characteristics of the dataset and present the comparison of several baseline algorithms trained on the data.
Session-based Hotel Recommendations Dataset: As part of the ACM Recommender System Challenge 2019 / Adamczak, Jens; Deldjoo, Yashar; Moghaddam, Farshad Bakhshandegan; Knees, Peter; Leyson, Gerard-Paul; Monreal, Philipp. - In: ACM TRANSACTIONS ON INTELLIGENT SYSTEMS AND TECHNOLOGY. - ISSN 2157-6904. - STAMPA. - 12:1(2021). [10.1145/3412379]
Session-based Hotel Recommendations Dataset: As part of the ACM Recommender System Challenge 2019
Deldjoo, Yashar;
2021-01-01
Abstract
In 2019, the Recommender Systems Challenge [17] dealt for the first time with a real-world task from the area of e-tourism, namely the recommendation of hotels in booking sessions. In this context, we present the release of a new dataset that we believe is vitally important for recommendation systems research in the area of hotel search, from both academic and industry perspectives. In this article, we describe the qualitative characteristics of the dataset and present the comparison of several baseline algorithms trained on the data.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
