47 citations · 57 across the 3 of their papers we have counts for
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cs.SI2020★ 47 cited
From Optimizing Engagement to Measuring Value
Smitha Milli, Luca Belli, Moritz Hardt
Most recommendation engines today are based on predicting user engagement, e.g. predicting whether a user will click on an item or not. However, there is potentially a large gap be…
cs.SI2020★ 7 cited
Privacy-Aware Recommender Systems Challenge on Twitter's Home Timeline
Luca Belli, Sofia Ira Ktena, Alykhan Tejani +12
Recommender systems constitute the core engine of most social network platforms nowadays, aiming to maximize user satisfaction along with other key business objectives. Twitter is…