Diagnosing Bias in Recommender Systems

Daniil, Savvina

In this project, we experiment with detecting popularity bias in recommender systems using the frameworks Lenskit and Cornac, and testing the algorithms UserKNN and BMF.

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Organisation	Human-Centered Data Analytics
Citation APA Style AAA Style APA Style Cell Style Chicago Style Harvard Style IEEE Style MLA Style Nature Style Vancouver Style American-Institute-of-Physics Style Council-of-Science-Editors Style BibTex Format Endnote Format RIS Format CSL Format DOIs only Format	Daniil, S. (2025). Diagnosing Bias in Recommender Systems.

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article On the challenges of studying bias in Recommender Systems: The effect of data characteristics and algorithm configuration S. Daniil (Savvina), M. Slokom (Manel), M. Cuper (Mirjam), C.C.S. Liem (Cynthia), J.R. van Ossenbruggen (Jacco) and L. Hollink (Laura)
software\|data Diagnosing Bias in Recommender Systems - Elliot S. Daniil (Savvina)

Diagnosing Bias in Recommender Systems

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article
On the challenges of studying bias in Recommender Systems: The effect of data characteristics and algorithm configuration

software|data
Diagnosing Bias in Recommender Systems - Elliot

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Diagnosing Bias in Recommender Systems

Publication

Publication

article On the challenges of studying bias in Recommender Systems: The effect of data characteristics and algorithm configuration

software|data Diagnosing Bias in Recommender Systems - Elliot

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article
On the challenges of studying bias in Recommender Systems: The effect of data characteristics and algorithm configuration

software|data
Diagnosing Bias in Recommender Systems - Elliot