Humanities scholars require recommender user models for digital archives that account for context volatility, epistemic trust, contrastive seeking, and strand continuity instead of stable preferences and session-bounded interactions.
De-centering the (Traditional) User: Multistake- holder Evaluation of Recommender Systems
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The thesis identifies theoretical, empirical, and conceptual flaws in offline fairness measures for recommender systems and contributes new evaluation methods and practical guidelines.
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What Do Humanities Scholars Need? A User Model for Recommendation in Digital Archives
Humanities scholars require recommender user models for digital archives that account for context volatility, epistemic trust, contrastive seeking, and strand continuity instead of stable preferences and session-bounded interactions.
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Offline Evaluation Measures of Fairness in Recommender Systems
The thesis identifies theoretical, empirical, and conceptual flaws in offline fairness measures for recommender systems and contributes new evaluation methods and practical guidelines.