conference-paper
Open access
User-oriented Fairness in Recommendation
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- Citations
- 209
- References
- 59
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- 0
Paper overview
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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