| 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 | 182* | 2019 |
| 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 | 31 | 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 | 21 | 2018 |
| 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 | 17* | 2021 |
| 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 | 5 | 2019 |
| 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 | 4 | 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 | 3* | 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 | 3* | 2018 |
| Methodological Issues in Recommender Systems Research M Ferrari Dacrema, P Cremonesi, D Jannach Proceedings of the Twenty-Ninth International Joint Conference on Artificial …, 2020 | 2 | 2020 |
| 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 | 2 | 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 | 2 | 2019 |
| Eigenvalue analogy for confidence estimation in item-based recommender systems M Ferrari Dacrema, P Cremonesi Proceedings of the Late-Breaking Results track part of the Twelfth ACM …, 2018 | 1* | 2018 |
| User Preference Sources: Explicit vs. Implicit Feedback P Cremonesi, F Garzotto, M Ferrari Dacrema Collaborative Recommendations, 233-252, 2018 | 1 | 2018 |
| Demonstrating the Equivalence of List Based and Aggregate Metrics to Measure the Diversity of Recommendations (Student Abstract) M Ferrari Dacrema Proceedings of The Thirty-Fifth AAAI Conference on Artificial Intelligence …, 2021 | | 2021 |
| 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 | | 2020 |
| 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 | | 2020 |
| On the effectiveness of convolutional neural networks in modelling latent dimensions interactions for recommender systems F PARRONI Italy, 2019 | | 2019 |
| Rating aware feature selection in content-based recommender systems A Cano Italy, 2019 | | 2019 |
| Eigenvalues as confidence estimators in item based recommender systems S ANTENUCCI, E CHIOSO Italy, 2019 | | 2019 |
| Automated feature engineering for recommender systems I INAJJAR, G LOCCI Italy, 2018 | | 2018 |
Paolo CremonesiDept. Computer Engineering, Politecnico di MilanoVerified email at polimi.it
