Algorithmic bias Algorithmic fairness Recommender systems

From the Beatles to Billie Eilish: Connecting Provider Representativeness and Exposure in Session-Based Recommender Systems

The size of a provider’s catalog in a platform affects the exposure that will be given to that provider by session-based recommender systems. Small providers, that are as popular as the big ones, are likely to get under-exposed in the recommendations. In an ECIR 2021 paper, with Alejandro Ariza, Francesco Fabbri, and Maria Salamó, we highlight side effects …

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Algorithmic bias Recommender systems

Connecting user and item perspectives in popularity debiasing for collaborative recommendation

The probability of recommending an item and of this recommendation being successful are biased against item popularity. By minimizing the correlation between a positive user-item interaction and the item’s popularity, we can avoid popularity bias. The recommendation of less popular items can come without affecting recommendation effectiveness and with a positive effect on other beyond-accuracy …

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