ContentWise Impressions: An Industrial Dataset with Impressions Included
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Abstract (arXiv)
In this article, we introduce the ContentWise Impressions dataset, a collection of implicit interactions and impressions of movies and TV series from an Over-The-Top media service, which delivers its media contents over the Internet. The dataset is distinguished from other already available multimedia recommendation datasets by the availability of impressions, i.e., the recommendations shown to the user, its size, and by being open-source. We describe the data collection process, the preprocessing applied, its characteristics, and statistics when compared to other commonly used datasets. We also highlight several possible use cases and research questions that can benefit from the availability of user impressions in an open-source dataset. Furthermore, we release software tools to load and split the data, as well as examples of how to use both user interactions and impressions in several common recommendation algorithms.
Key facts. Cited by 8 papers in the map (data through 7 Oct 2026). First posted on arXiv 3 Aug 2020.
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Citing papers per year: 2021: 2; 2022: 0; 2023: 1; 2024: 3; 2025: 1; 2026: 1.
8 papers.
- 2024Deep Evolutional Instant Interest Network for CTR Prediction in Trigger-Induced Recommendationcited by 3
- 2023Impression-Aware Recommender Systemscited by 1
- 2024Neural Click Models for Recommender Systemscited by 1
- 2021A Methodology for the Offline Evaluation of Recommender Systems in a User Interface with Multiple Carouselscited by 0
- 2021Measuring the User Satisfaction in a Recommendation Interface with Multiple Carouselscited by 0
- 2024Modeling Social Media Recommendation Impacts Using Academic Networks: A Graph Neural Network Approachcited by 0
- 2025On the Reliability of Sampling Strategies in Offline Recommender Evaluationcited by 0
- 2026FARE: Deep Reinforcement Learning For Fair Exposure Constrained Uncertainty Aware Financial Content Personalizationcited by 0
- 2026FARE: Deep Reinforcement Learning For Fair Exposure Constrained Uncertainty Aware Financial Content Personalization25 Sep 2026
- 2025On the Reliability of Sampling Strategies in Offline Recommender Evaluation7 Aug 2025
- 2024Modeling Social Media Recommendation Impacts Using Academic Networks: A Graph Neural Network Approach6 Oct 2024
- 2024Neural Click Models for Recommender Systems30 Sep 2024
- 2024Deep Evolutional Instant Interest Network for CTR Prediction in Trigger-Induced Recommendation15 Jan 2024
- 2023Impression-Aware Recommender Systems15 Aug 2023
- 2021Measuring the User Satisfaction in a Recommendation Interface with Multiple Carousels14 May 2021
- 2021A Methodology for the Offline Evaluation of Recommender Systems in a User Interface with Multiple Carousels13 May 2021