3 papers
cs.IR2024
Embedding Cultural Diversity in Prototype-based Recommender Systems
Armin Moradi, Nicola Neophytou, Florian Carichon +1
Popularity bias in recommender systems can increase cultural overrepresentation by favoring norms from dominant cultures and marginalizing underrepresented groups. This issue is cr…
cs.IR2024
Advancing Cultural Inclusivity: Optimizing Embedding Spaces for Balanced Music Recommendations
Armin Moradi, Nicola Neophytou, Golnoosh Farnadi
Popularity bias in music recommendation systems -- where artists and tracks with the highest listen counts are recommended more often -- can also propagate biases along demographic…
cs.IR2023
Tidying Up the Conversational Recommender Systems' Biases
Armin Moradi, Golnoosh Farnadi
The growing popularity of language models has sparked interest in conversational recommender systems (CRS) within both industry and research circles. However, concerns regarding bi…