# Diversifying Music Recommendations

arXiv: https://arxiv.org/abs/1810.01482 · HTML: https://mlsanity.com/paper/1810.01482/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Oct 2018.

## Built on by (most cited first, 2 of 2)

- [Beyond NDCG: behavioral testing of recommender systems with RecList](https://mlsanity.com/paper/2111.09963/) (2021)
- [Online Two-Stage Submodular Maximization](https://mlsanity.com/paper/2510.19480/) (2025)

## Abstract (arXiv)

We compare submodular and Jaccard methods to diversify Amazon Music recommendations. Submodularity significantly improves recommendation quality and user engagement. Unlike the Jaccard method, our submodular approach incorporates item relevance score within its optimization function, and produces a relevant and uniformly diverse set.