Recommending without short head
Author:
Affiliation:
1. Politecnico di Milano, Milan, Italy
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/2567948.2577286
Reference6 articles.
1. Investigating the Persuasion Potential of Recommender Systems from a Quality Perspective
2. My head is your tail
3. Collaborative prediction and ranking with non-random missing data
4. Ranking with non-random missing ratings
5. A user-centric evaluation framework for recommender systems
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1. A survey on popularity bias in recommender systems;User Modeling and User-Adapted Interaction;2024-07-01
2. Evaluating The Effects of Calibrated Popularity Bias Mitigation: A Field Study;Proceedings of the 17th ACM Conference on Recommender Systems;2023-09-14
3. Timestamp Prediction Using Enhanced Adaptive Correlation Clustering-Based Recommender System for the Long Tail Items;Advances in Cognitive Science and Communications;2023
4. Connecting user and item perspectives in popularity debiasing for collaborative recommendation;Information Processing & Management;2021-01
5. An Adaptive Correlation Clustering-Based Recommender System for the Long-Tail Items;Smart Computing Techniques and Applications;2021
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