# Mr. DLib: Recommendations-as-a-Service (RaaS) for Academia

arXiv: https://arxiv.org/abs/1703.09108 · HTML: https://mlsanity.com/paper/1703.09108/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Mar 2017.

## Built on by (most cited first, 1 of 1)

- [Algorithm Selection for Recommender Systems via Meta-Learning on Algorithm Characteristics](https://mlsanity.com/paper/2508.04419/) (2025)

## Abstract (arXiv)

Only few digital libraries and reference managers offer recommender systems, although such systems could assist users facing information overload. In this paper, we introduce Mr. DLib's recommendations-as-a-service, which allows third parties to easily integrate a recommender system into their products. We explain the recommender approaches implemented in Mr. DLib (content-based filtering among others), and present details on 57 million recommendations, which Mr. DLib delivered to its partner GESIS Sowiport. Finally, we outline our plans for future development, including integration into JabRef, establishing a living lab, and providing personalized recommendations.