MovieLens

Introduced by F. Maxwell Harper et al. in The MovieLens Datasets: History and Context

The MovieLens datasets, first released in 1998, describe people’s expressed preferences for movies. These preferences take the form of tuples, each the result of a person expressing a preference (a 0-5 star rating) for a movie at a particular time. These preferences were entered by way of the MovieLens web site1 — a recommender system that asks its users to give movie ratings in order to receive personalized movie recommendations.

Source: The MovieLens Datasets: History and Context

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Benchmarks

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Task	Dataset Variant	Best Model
Recommendation Systems	MovieLens 1M	GLocal-K
Recommendation Systems	MovieLens 20M	VASP
Recommendation Systems	MovieLens 100K	GHRS
Recommendation Systems	MovieLens 10M	Bayesian timeSVD++ flipped
Link Prediction	MovieLens 25M	PEAGAT
Click-Through Rate Prediction	MovieLens 20M	github.com/guotong1988/movielens_dataset
Click-Through Rate Prediction	MovieLens 1M	STEC
Movie Recommendation	MovieLens 1M	BPR
Explainable Recommendation	MovieLens 1M	R-PGPR
Click-Through Rate Prediction	MovieLens	FinalMLP
Sequential Recommendation	MovieLens 1M	BSARec
Recommendation Systems	MovieLens-Latest	RATE-CSE
Recommendation Systems (Item cold-start)	MovieLens 10M	scaled-CER
Multi-Media Recommendation	MovieLens 10M	MMGCN
Knowledge Graph Completion	MovieLens 1M	KTUP
Multi-Media Recommendation	MovieLens	LightGT