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The MovieLens Beliefs Dataset: Collecting Pre-Choice Data for Online Recommender Systems
An increasingly important aspect of designing recommender systems involves considering how recommendations will influence consumer choices.
The Economics of Recommender Systems: Evidence from a Field Experiment on MovieLens
We conduct a field experiment on a movie-recommendation platform to identify if and how recommendations affect consumption.
Toward the Next Generation of News Recommender Systems
This paper proposes a vision and research agenda for the next generation of news recommender systems (RS), called the table d'hote approach.
Developing a Recommendation Benchmark for MLPerf Training and Inference
Deep learning-based recommendation models are used pervasively and broadly, for example, to recommend movies, products, or other information most relevant to users, in order to enhance the user experience.
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