BORATTO, LUDOVICO
BORATTO, LUDOVICO
DIPARTIMENTO DI MATEMATICA ED INFORMATICA
Conclusions
2024-01-01 Felfernig, A.; Boratto, L.; Stettinger, M.; Tkalcic, M.
Evaluating Group Recommender Systems
2024-01-01 Trattner, C.; Said, A.; Boratto, L.; Felfernig, A.
Bias characterization, assessment, and mitigation in location-based recommender systems
2023-01-01 Sanchez, P.; Bellogin, A.; Boratto, L.
Consumer Fairness Benchmark in Recommendation
2023-01-01 Boratto, L.; Fenu, G.; Marras, M.; Medda, G.
Counterfactual Graph Augmentation for Consumer Unfairness Mitigation in Recommender Systems
2023-01-01 Boratto, L.; Fabbri, F.; Fenu, G.; Marras, M.; Medda, G.
FairUP: A Framework for Fairness Analysis of Graph Neural Network-Based User Profiling Models
2023-01-01 Abdelrazek, M.; Purificato, E.; Boratto, L.; De Luca, E. W.
First Workshop on User Perspectives in Human-Centred Artificial Intelligence (HCAI4U)
2023-01-01 De Luca, E. W.; Purificato, E.; Boratto, L.; Marrone, S.; Sansone, C.
Fourth International Workshop on Algorithmic Bias in Search and Recommendation (Bias 2023)
2023-01-01 Boratto, L.; Faralli, S.; Marras, M.; Stilo, G.
HCAI4U 2023 - Preface to the First Workshop on User Perspectives in Human-Centred Artificial Intelligence
2023-01-01 De Luca, E. W.; Purificato, E.; Boratto, L.; Marrone, S.; Sansone, C.
Knowledge is Power, Understanding is Impact: Utility and Beyond Goals, Explanation Quality, and Fairness in Path Reasoning Recommendation
2023-01-01 Balloccu, G.; Boratto, L.; Cancedda, C.; Fenu, G.; Marras, M.
Knowledge-aware Recommendations: Exploring the Interplay between Utility, Explanation Quality, and Fairness in Path Reasoning Methods
2023-01-01 Balloccu, G.; Boratto, L.; Cancedda, C.; Fenu, G.; Marras, M.
Leveraging Graph Neural Networks for User Profiling: Recent Advances and Open Challenges
2023-01-01 Purificato, E.; Boratto, L.; De Luca, E. W.
Looks Can Be Deceiving: Linking User-Item Interactions and User's Propensity Towards Multi-Objective Recommendations
2023-01-01 Dokoupil, P.; Peska, L.; Boratto, L.
Looks Can Be Deceiving: Linking User-Item Interactions and User’s Propensity Towards Multi-Objective Recommendations
2023-01-01 Dokoupil, Patrik; Peska, Ladislav; Boratto, Ludovico
Practical perspectives of consumer fairness in recommendation
2023-01-01 Boratto, L.; Fenu, G.; Marras, M.; Medda, G.
Recent Advances in Fairness Analysis of User Profiling Approaches in E-Commerce with Graph Neural Networks
2023-01-01 Purificato, E.; Boratto, L.; De Luca, E. W.
Reinforcement recommendation reasoning through knowledge graphs for explanation path quality
2023-01-01 Balloccu, G.; Boratto, L.; Fenu, G.; Marras, M.
Reproducibility of Multi-Objective Reinforcement Learning Recommendation: Interplay between Effectiveness and Beyond-Accuracy Perspectives
2023-01-01 Paparella, Vincenzo; Anelli, Vito Walter; Boratto, Ludovico; Di Noia, Tommaso
Rows or Columns? Minimizing Presentation Bias When Comparing Multiple Recommender Systems
2023-01-01 Dokoupil, P.; Peska, L.; Boratto, L.
Towards Explainable Educational Recommendation through Path Reasoning Methods
2023-01-01 Afreen, N.; Balloccu, G.; Boratto, L.; Fenu, G.; Marras, M.
| Titolo | Data di pubblicazione | Autore(i) | Rivista | Editore |
|---|---|---|---|---|
| Conclusions | 1-gen-2024 | Felfernig, A.; Boratto, L.; Stettinger, M.; Tkalcic, M. | - | Springer Science and Business Media Deutschland GmbH |
| Evaluating Group Recommender Systems | 1-gen-2024 | Trattner, C.; Said, A.; Boratto, L.; Felfernig, A. | - | Springer Science and Business Media Deutschland GmbH |
| Bias characterization, assessment, and mitigation in location-based recommender systems | 1-gen-2023 | Sanchez, P.; Bellogin, A.; Boratto, L. | DATA MINING AND KNOWLEDGE DISCOVERY | - |
| Consumer Fairness Benchmark in Recommendation | 1-gen-2023 | Boratto, L.; Fenu, G.; Marras, M.; Medda, G. | - | CEUR-WS |
| Counterfactual Graph Augmentation for Consumer Unfairness Mitigation in Recommender Systems | 1-gen-2023 | Boratto, L.; Fabbri, F.; Fenu, G.; Marras, M.; Medda, G. | - | Association for Computing Machinery |
| FairUP: A Framework for Fairness Analysis of Graph Neural Network-Based User Profiling Models | 1-gen-2023 | Abdelrazek, M.; Purificato, E.; Boratto, L.; De Luca, E. W. | - | Association for Computing Machinery |
| First Workshop on User Perspectives in Human-Centred Artificial Intelligence (HCAI4U) | 1-gen-2023 | De Luca, E. W.; Purificato, E.; Boratto, L.; Marrone, S.; Sansone, C. | - | Association for Computing Machinery |
| Fourth International Workshop on Algorithmic Bias in Search and Recommendation (Bias 2023) | 1-gen-2023 | Boratto, L.; Faralli, S.; Marras, M.; Stilo, G. | - | Springer Science and Business Media Deutschland GmbH |
| HCAI4U 2023 - Preface to the First Workshop on User Perspectives in Human-Centred Artificial Intelligence | 1-gen-2023 | De Luca, E. W.; Purificato, E.; Boratto, L.; Marrone, S.; Sansone, C. | - | CEUR-WS |
| Knowledge is Power, Understanding is Impact: Utility and Beyond Goals, Explanation Quality, and Fairness in Path Reasoning Recommendation | 1-gen-2023 | Balloccu, G.; Boratto, L.; Cancedda, C.; Fenu, G.; Marras, M. | - | Springer Science and Business Media Deutschland GmbH |
| Knowledge-aware Recommendations: Exploring the Interplay between Utility, Explanation Quality, and Fairness in Path Reasoning Methods | 1-gen-2023 | Balloccu, G.; Boratto, L.; Cancedda, C.; Fenu, G.; Marras, M. | - | CEUR-WS |
| Leveraging Graph Neural Networks for User Profiling: Recent Advances and Open Challenges | 1-gen-2023 | Purificato, E.; Boratto, L.; De Luca, E. W. | - | Association for Computing Machinery |
| Looks Can Be Deceiving: Linking User-Item Interactions and User's Propensity Towards Multi-Objective Recommendations | 1-gen-2023 | Dokoupil, P.; Peska, L.; Boratto, L. | - | Association for Computing Machinery, Inc |
| Looks Can Be Deceiving: Linking User-Item Interactions and User’s Propensity Towards Multi-Objective Recommendations | 1-gen-2023 | Dokoupil, Patrik; Peska, Ladislav; Boratto, Ludovico | - | ACM, Association for Computing Machinery |
| Practical perspectives of consumer fairness in recommendation | 1-gen-2023 | Boratto, L.; Fenu, G.; Marras, M.; Medda, G. | INFORMATION PROCESSING & MANAGEMENT | - |
| Recent Advances in Fairness Analysis of User Profiling Approaches in E-Commerce with Graph Neural Networks | 1-gen-2023 | Purificato, E.; Boratto, L.; De Luca, E. W. | - | CEUR-WS |
| Reinforcement recommendation reasoning through knowledge graphs for explanation path quality | 1-gen-2023 | Balloccu, G.; Boratto, L.; Fenu, G.; Marras, M. | KNOWLEDGE-BASED SYSTEMS | - |
| Reproducibility of Multi-Objective Reinforcement Learning Recommendation: Interplay between Effectiveness and Beyond-Accuracy Perspectives | 1-gen-2023 | Paparella, Vincenzo; Anelli, Vito Walter; Boratto, Ludovico; Di Noia, Tommaso | - | Association for Computing Machinery |
| Rows or Columns? Minimizing Presentation Bias When Comparing Multiple Recommender Systems | 1-gen-2023 | Dokoupil, P.; Peska, L.; Boratto, L. | - | Association for Computing Machinery |
| Towards Explainable Educational Recommendation through Path Reasoning Methods | 1-gen-2023 | Afreen, N.; Balloccu, G.; Boratto, L.; Fenu, G.; Marras, M. | - | CEUR-WS |