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Top-N Recommendation Algorithms: A Quest for the State-of-the-Art

, , , , and . Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization, page 121-131. ACM, (July 2022)
DOI: 10.1145/3503252.3531292

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Exposing Open Street Map in the Linked Data cloud., , , , , and . SEBD, page 302-309. Matematicamente.it, (2016)Time and Local Popularity in top-N Recommendation., , , , and . CoRR, (2018)Multi-Step Adversarial Perturbations on Recommender Systems Embeddings., , , , and . CoRR, (2020)Reshaping Graph Recommendation with Edge Graph Collaborative Filtering and Customer Reviews., , , , , , and . DL4SR@CIKM, volume 3317 of CEUR Workshop Proceedings, CEUR-WS.org, (2022)Adherence and Constancy in LIME-RS Explanations for Recommendation., , , , , and . CoRR, (2021)Counterfactual Fair Opportunity: Measuring Decision Model Fairness with Counterfactual Reasoning., , , , and . CoRR, (2023)Counterfactual Reasoning for Decision Model Fairness Assessment., , , , and . WWW (Companion Volume), page 229-233. ACM, (2023)How to Perform Reproducible Experiments in the ELLIOT Recommendation Framework: Data Processing, Model Selection, and Performance Evaluation., , , , , , , , and . IIR, volume 2947 of CEUR Workshop Proceedings, CEUR-WS.org, (2021)Counterfactual Reasoning for Responsible AI Assessment., , , , and . Ital-IA, volume 3486 of CEUR Workshop Proceedings, page 347-352. CEUR-WS.org, (2023)Adversarial Recommender Systems: Attack, Defense, and Advances., , , and . Recommender Systems Handbook, Springer US, (2022)