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Ludovico Boratto

Research scientist

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Day: July 24, 2023

Algorithmic fairness Recommender systems

The Winner Takes it All: Geographic Imbalance and Provider (Un)fairness in Educational Recommender Systems

The fact that most of the courses in MOOC platforms are offered by American teachers leads to the over-recommendation of these courses, at the expense of the courses produced in the other countries. A re-ranking that accounts for the country of production of a course, besides the relevance of the course for a user, is …

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Algorithmic fairness Recommender systems

Interplay between Upsampling and Regularization for Provider Fairness in Recommender Systems

In the presence of a minority group of item providers in the data (characterized by a sensitive attribute, such as gender or age), the items of these providers are considered as of lower relevance and are recommended to the users with a lower visibility (i.e., fewer times) and a lower exposure (i.e., in lower positions …

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About me

I am a research scientist with a background on Information Retrieval. Most of my research involves discovering patterns in user behavior, to provide useful information to the users. I have worked on recommender systems, clustering algorithms, social media analysis, and natural language processing.

My current research interests focus on algorithmic bias on the Web, to generate fair and non-discriminating rankings.

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