Rows or Columns? Minimizing Presentation Bias When Comparing Multiple Recommender Systems
Author:
Affiliation:
1. Faculty of Mathematics and Physics, Charles University, Prague, Czech Rep
2. University of Cagliari, Cagliari, Italy
Funder
Charles University Grant Agency
Charles University
Czech Science Foundation
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3539618.3592056
Reference9 articles.
1. Explainability in music recommender systems
2. A pragmatic procedure to support the user-centric evaluation of recommender systems
3. Impact of item consumption on assessment of recommendations in user studies
4. Primacy and Recency Effects on Clicking Behavior
5. Towards Results-level Proportionality for Multi-objective Recommender Systems
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1. SM-RS: Single- and Multi-Objective Recommendations with Contextual Impressions and Beyond-Accuracy Propensity Scores;Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval;2024-07-10
2. MOReGIn: Multi-Objective Recommendation at the Global and Individual Levels;Lecture Notes in Computer Science;2024
3. EasyStudy: Framework for Easy Deployment of User Studies on Recommender Systems;Proceedings of the 17th ACM Conference on Recommender Systems;2023-09-14
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