Biases in Scholarly Recommender Systems: Impact, Prevalence, and Mitigation

no code implementations • 18 Jan 2023 • Michael Färber, Melissa Coutinho, Shuzhou Yuan

With the remarkable increase in the number of scientific entities such as publications, researchers, and scientific topics, and the associated information overload in science, academic recommender systems have become increasingly important for millions of researchers and science enthusiasts.

Recommendation Systems