An Image Dataset for Benchmarking Recommender Systems with Raw Pixels

Understand

Recommender systems (RS) have achieved significant success by leveraging explicit identification (ID) features.

• However, the full potential of content features, especially the pure image pixel features, remains relatively unexplored.
• The limited availability of large, diverse, and content-driven image recommendation datasets has hindered the use of raw images as item representations.
• In this regard, we present PixelRec, a massive image-centric recommendation dataset that includes approximately 200 million user-image interactions, 30 million users, and 400,000 high-quality cover images.