ContentWise Impressions: An Industrial Dataset with Impressions Included

TL;DR

This paper introduces the ContentWise Impressions dataset, an open-source collection of user interactions and impressions from an OTT media service, enabling new research in multimedia recommendation systems.

Contribution

It provides a large, open-source dataset with impressions included, along with tools and examples for research in recommendation algorithms.

Findings

Dataset includes implicit interactions and impressions from OTT media.

Tools provided for data loading and splitting.

Facilitates research on impression-based recommendation methods.

Abstract

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.