| Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches M Ferrari Dacrema, P Cremonesi, D Jannach Proceedings of the 13th ACM Conference on Recommender Systems (RecSys 2019), 2019 | 517 | 2019 |
| A Troubling Analysis of Reproducibility and Progress in Recommender Systems Research M Ferrari Dacrema, S Boglio, P Cremonesi, D Jannach ACM Transactions on Information Systems, 2021 | 128 | 2021 |
| Movie Genome: Alleviating New Item Cold Start in Movie Recommendation Y Deldjoo, M Ferrari Dacrema, M Gabriel Constantin, H Eghbal-Zadeh, ... User Modeling and User-Adapted Interaction (UMUAI), 2019 | 76 | 2019 |
| Artist-driven layering and user's behaviour impact on recommendations in a playlist continuation scenario S Antenucci, S Boglio, E Chioso, E Dervishaj, S Kang, T Scarlatti, ... Proceedings of the ACM Recommender Systems Challenge 2018, 4, 2018 | 24 | 2018 |
| Critically Examining the Claimed Value of Convolutions over User-Item Embedding Maps for Recommender Systems M Ferrari Dacrema, F Parroni, P Cremonesi, D Jannach Proceedings of the 29th ACM International Conference on Information and …, 2020 | 21 | 2020 |
| Feature Selection for Recommender Systems with Quantum Computing R Nembrini, M Ferrari Dacrema, P Cremonesi Entropy 23 (8), 970, 2021 | 15 | 2021 |
| ContentWise Impressions: An industrial dataset with impressions included FB Pérez Maurera, M Ferrari Dacrema, L Saule, M Scriminaci, ... Proceedings of the 29th ACM International Conference on Information and …, 2020 | 15 | 2020 |
| A Methodology for the Offline Evaluation of Recommender Systems in a User Interface with Multiple Carousels N Felicioni, M Ferrari Dacrema, P Cremonesi Adjunct Proceedings of the 29th ACM Conference on User Modeling, Adaptation …, 2021 | 14 | 2021 |
| A novel graph-based model for hybrid recommendations in cold-start scenarios C Bernardis, M Ferrari Dacrema, P Cremonesi Proceedings of the Late-Breaking Results track part of the Twelfth ACM …, 2018 | 13* | 2018 |
| Leveraging laziness, browsing-pattern aware stacked models for sequential accommodation learning to rank E D'Amico, G Gabbolini, D Montesi, M Moreschini, F Parroni, F Piccinini, ... Proceedings of the Workshop on ACM Recommender Systems Challenge, 1-5, 2019 | 10 | 2019 |
| Estimating Confidence of Individual User Predictions in Item-based Recommender Systems C Bernardis, M Ferrari Dacrema, P Cremonesi Proceedings of the 27th ACM Conference on User Modeling, Adaptation and …, 2019 | 10 | 2019 |
| Optimizing the Selection of Recommendation Carousels with Quantum Computing M Ferrari Dacrema, N Felicioni, P Cremonesi Fifteenth ACM Conference on Recommender Systems (RecSys ’21), 2021 | 9 | 2021 |
| Evaluating the job shop scheduling problem on a D-wave quantum annealer C Carugno, M Ferrari Dacrema, P Cremonesi Nature Scientific Reports 12 (1), 2022 | 8* | 2022 |
| Multi-Objective Blended Ensemble For Highly Imbalanced Sequence Aware Tweet Engagement Prediction N Felicioni, A Donati, L Conterio, L Bartoccioni, DYX Hu, C Bernardis, ... Proceedings of the Recommender Systems Challenge 2020, 29-33, 2020 | 8 | 2020 |
| Deriving item features relevance from collaborative domain knowledge M Ferrari Dacrema, A Gasparin, P Cremonesi Proceedings of KaRS 2018 Workshop on Knowledge-aware and Conversational …, 2018 | 8* | 2018 |
| Towards Feature Selection for Ranking and Classification Exploiting Quantum Annealers M Ferrari Dacrema, F Moroni, R Nembrini, N Ferro, G Faggioli, ... Proceedings of the 45th International ACM SIGIR Conference on Research and …, 2022 | 7 | 2022 |
| Methodological Issues in Recommender Systems Research M Ferrari Dacrema, P Cremonesi, D Jannach Proceedings of the Twenty-Ninth International Joint Conference on Artificial …, 2020 | 6 | 2020 |
| Aggregating Models for Anomaly Detection in Space Systems: Results from the FCTMAS Study F Amigoni, M Ferrari Dacrema, A Donati, C Laroque, M Lavagna, A Riva International Conference on Intelligent Autonomous Systems, 142-160, 2018 | 5 | 2018 |
| Towards Evaluating User Profiling Methods Based on Explicit Ratings on Item Features LL Costanzo, Y Deldjoo, MF Dacrema, M Schedl, P Cremonesi IntRS workshop, The 13th ACM Conference on Recommender Systems (RecSys …, 2019 | 4 | 2019 |
| Design and Evaluation of Cross-domain Recommender Systems M Ferrari Dacrema, I Cantador, I Fernández-Tobıas, S Berkovsky, ... Recommender systems handbook, 2022 | 3* | 2022 |
Paolo CremonesiDept. Computer Engineering, Politecnico di MilanoEmail verificata su polimi.it
