Session-based Hotel Recommendations Dataset

Author:

Adamczak Jens1,Deldjoo Yashar2ORCID,Moghaddam Farshad Bakhshandegan3,Knees Peter4,Leyson Gerard-Paul5,Monreal Philipp5

Affiliation:

1. trivago N.V., Germany

2. Polytechnic University of Bari, Italy

3. Karlsruhe Institute of Technology, Germany

4. TU Wien, Austria

5. trivago N.V.,Germany

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.

Publisher

Association for Computing Machinery (ACM)

Subject

Artificial Intelligence,Theoretical Computer Science

Cited by 12 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Deep click interest network for reranking hotels;Engineering Applications of Artificial Intelligence;2024-04

2. CAPRI: Context-aware point-of-interest recommendation framework;Software Impacts;2024-03

3. A Dataset of Hotel Reviews for Aspect-Based Sentiment Analysis and Topic Modeling;2023 18th International Workshop on Semantic and Social Media Adaptation & Personalization (SMAP)18th International Workshop on Semantic and Social Media Adaptation & Personalization (SMAP 2023);2023-09-25

4. FFM-SVD: A Novel Approach for Personality-aware Recommender Systems;2022 IEEE/ACS 19th International Conference on Computer Systems and Applications (AICCSA);2022-12

5. The role of context fusion on accuracy, beyond-accuracy, and fairness of point-of-interest recommendation systems;Expert Systems with Applications;2022-11

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