  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.
