conference-paper Open access

User-oriented Fairness in Recommendation

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Abstract

As a highly data-driven application, recommender systems could be affected by data bias, resulting in unfair results for different data groups, which could be a reason that affects the system performance. Therefore, it is important to identify and solve the unfairness issues in recommendation scenarios.

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Publication details

DOI
10.1145/3442381.3449866
OpenAlex
W3153182568
Document type
conference-paper
Language
EN
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