| Personalizing session-based recommendations with hierarchical recurrent neural networks M Quadrana, A Karatzoglou, B Hidasi, P Cremonesi Proceedings of the Eleventh ACM Conference on Recommender Systems, 130-137, 2017 | 309 | 2017 |
| Parallel recurrent neural network architectures for feature-rich session-based recommendations B Hidasi, M Quadrana, A Karatzoglou, D Tikk Proceedings of the 10th ACM conference on recommender systems, 241-248, 2016 | 276 | 2016 |
| Sequence-aware recommender systems M Quadrana, P Cremonesi, D Jannach ACM Computing Surveys (CSUR) 51 (4), 1-36, 2018 | 250 | 2018 |
| Content-based video recommendation system based on stylistic visual features Y Deldjoo, M Elahi, P Cremonesi, F Garzotto, P Piazzolla, M Quadrana Journal on Data Semantics 5 (2), 99-113, 2016 | 138 | 2016 |
| Cross-domain recommendations without overlapping data: Myth or reality? P Cremonesi, M Quadrana Proceedings of the 8th ACM Conference on Recommender systems, 297-300, 2014 | 46 | 2014 |
| Using visual features based on MPEG-7 and deep learning for movie recommendation Y Deldjoo, M Elahi, M Quadrana, P Cremonesi International journal of multimedia information retrieval 7 (4), 207-219, 2018 | 43 | 2018 |
| 30Music Listening and Playlists Dataset. R Turrin, M Quadrana, A Condorelli, R Pagano, P Cremonesi RecSys Posters, 2015 | 42 | 2015 |
| The contextual turn: From context-aware to context-driven recommender systems R Pagano, P Cremonesi, M Larson, B Hidasi, D Tikk, A Karatzoglou, ... Proceedings of the 10th ACM conference on recommender systems, 249-252, 2016 | 32 | 2016 |
| An efficient closed frequent itemset miner for the MOA stream mining system M Quadrana, A Bifet, R Gavalda AI Communications 28 (1), 143-158, 2015 | 17 | 2015 |
| An efficient closed frequent itemset miner for the MOA stream mining system M Quadrana, A Bifet, R Gavalda AI Communications 28 (1), 143-158, 2015 | 17 | 2015 |
| Toward effective movie recommendations based on mise-en-scčne film styles Y Deldjoo, M Elahi, M Quadrana, P Cremonesi, F Garzotto Proceedings of the 11th biannual conference on italian sigchi chapter, 162-165, 2015 | 16 | 2015 |
| The Importance of Song Context in Music Playlists. A Vall, M Quadrana, M Schedl, G Widmer, P Cremonesi RecSys Posters, 2017 | 15 | 2017 |
| The effect of different video summarization models on the quality of video recommendation based on low-level visual features Y Deldjoo, P Cremonesi, M Schedl, M Quadrana Proceedings of the 15th International Workshop on Content-Based Multimedia …, 2017 | 14 | 2017 |
| Recommending without short head P Cremonesi, F Garzotto, R Pagano, M Quadrana Proceedings of the 23rd International Conference on World Wide Web, 245-246, 2014 | 14 | 2014 |
| Order, context and popularity bias in next-song recommendations A Vall, M Quadrana, M Schedl, G Widmer International Journal of Multimedia Information Retrieval 8 (2), 101-113, 2019 | 10 | 2019 |
| Deriving item features relevance from past user interactions L Cella, S Cereda, M Quadrana, P Cremonesi Proceedings of the 25th Conference on User Modeling, Adaptation and …, 2017 | 10 | 2017 |
| Evaluating top-n recommendations" when the best are gone" P Cremonesi, F Garzotto, M Quadrana Proceedings of the 7th ACM conference on Recommender systems, 339-342, 2013 | 10 | 2013 |
| Multi-stack ensemble for job recommendation T Carpi, M Edemanti, E Kamberoski, E Sacchi, P Cremonesi, R Pagano, ... Proceedings of the Recommender Systems Challenge, 1-4, 2016 | 9 | 2016 |
| Large scale music recommendation R Turrin, A Condorelli, P Cremonesi, R Pagano, M Quadrana Workshop on Large-Scale Recommender Systems (LSRS 2015) at ACM RecSys, 2015 | 8 | 2015 |
| The importance of song context and song order in automated music playlist generation A Vall, M Quadrana, M Schedl, G Widmer arXiv preprint arXiv:1807.04690, 2018 | 7 | 2018 |
Paolo CremonesiDept. Computer Engineering, Politecnico di MilanoVerified email at polimi.it
