| A dynamic collaborative filtering system via a weighted clustering approach A Salah, N Rogovschi, M Nadif Neurocomputing 175, 206-215, 2016 | 99 | 2016 |
| Cornac: A comparative framework for multimodal recommender systems A Salah, QT Truong, HW Lauw Journal of Machine Learning Research 21 (95), 1-5, 2020 | 77 | 2020 |
| Bilateral variational autoencoder for collaborative filtering QT Truong, A Salah, HW Lauw Proceedings of the 14th ACM International Conference on Web Search and Data …, 2021 | 66 | 2021 |
| Word co-occurrence regularized non-negative matrix tri-factorization for text data co-clustering A Salah, M Ailem, M Nadif Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 44 | 2018 |
| Directional co-clustering A Salah, M Nadif Advances in Data Analysis and Classification 13, 591-620, 2019 | 35 | 2019 |
| Non-negative matrix factorization meets word embedding M Ailem, A Salah, M Nadif Proceedings of the 40th international acm sigir conference on research and …, 2017 | 33 | 2017 |
| Social regularized von Mises–Fisher mixture model for item recommendation A Salah, M Nadif Data Mining and Knowledge Discovery 31, 1218-1241, 2017 | 21 | 2017 |
| Towards source-aligned variational models for cross-domain recommendation A Salah, TB Tran, H Lauw Proceedings of the 15th ACM Conference on Recommender Systems, 176-186, 2021 | 20 | 2021 |
| Model-based von mises-fisher co-clustering with a conscience A Salah, M Nadif Proceedings of the 2017 SIAM International Conference on Data Mining, 246-254, 2017 | 19 | 2017 |
| Multi-modal recommender systems: Hands-on exploration QT Truong, A Salah, H Lauw Proceedings of the 15th ACM Conference on Recommender Systems, 834-837, 2021 | 15 | 2021 |
| Model-based co-clustering for high dimensional sparse data A Salah, N Rogovschi, M Nadif Artificial intelligence and statistics, 866-874, 2016 | 11 | 2016 |
| Exploring cross-modality utilization in recommender systems QT Truong, A Salah, TB Tran, J Guo, HW Lauw IEEE Internet Computing 25 (4), 50-57, 2021 | 9 | 2021 |
| Probabilistic collaborative representation learning for personalized item recommendation A Salah, HW Lauw AUAI Press, 2018 | 9 | 2018 |
| A bayesian latent variable model of user preferences with item context A Salah, HW Lauw IJCAI, 2018 | 9 | 2018 |
| A way to boost semi-NMF for document clustering A Salah, M Ailem, M Nadif Proceedings of the 2017 ACM on Conference on Information and Knowledge …, 2017 | 8 | 2017 |
| Improving NMF clustering by leveraging contextual relationships among words M Febrissy, A Salah, M Ailem, M Nadif Neurocomputing 495, 105-117, 2022 | 4 | 2022 |
| Multi-modal attribute extraction for e-commerce A De la Comble, A Dutt, P Montalvo, A Salah arXiv preprint arXiv:2203.03441, 2022 | 4 | 2022 |
| Tutorials at the web conference 2023 V Fionda, O Hartig, R Abdolazimi, S Amer-Yahia, H Chen, X Chen, P Cui, ... Companion Proceedings of the ACM Web Conference 2023, 648-658, 2023 | 3 | 2023 |
| Stochastic co-clustering for document-term data A Salah, N Rogovschi, M Nadif Proceedings of the 2016 SIAM International Conference on Data Mining, 306-314, 2016 | 3 | 2016 |
| Von Mises-Fisher based (co-) clustering for high-dimensional sparse data: application to text and collaborative filtering data A Salah Université Sorbonne Paris Cité, 2016 | 1 | 2016 |
Mohamed NadifProfesseur - Université Paris Cité - Centre Borelli UMR 9010Verified email at u-paris.fr
