4 citations · 4 across the 2 of their papers we have counts for
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cs.IR2024★ 11 cited
Making Alice Appear Like Bob: A Probabilistic Preference Obfuscation Method For Implicit Feedback Recommendation Models
Gustavo Escobedo, Marta Moscati, Peter Muellner +4
Users' interaction or preference data used in recommender systems carry the risk of unintentionally revealing users' private attributes (e.g., gender or race). This risk becomes pa…
cs.IR2015★ 4 cited
Attention Please! A Hybrid Resource Recommender Mimicking Attention-Interpretation Dynamics
Paul Seitlinger, Dominik Kowald, Simone Kopeinik +3
Classic resource recommenders like Collaborative Filtering (CF) treat users as being just another entity, neglecting non-linear user-resource dynamics shaping attention and interpr…