| A systematic literature review of Linked Data‐based recommender systems C Figueroa, I Vagliano, OR Rocha, M Morisio Concurrency and Computation: Practice and Experience 27 (17), 4659-4684, 2015 | 72 | 2015 |
| Multi-modal adversarial autoencoders for recommendations of citations and subject labels L Galke, F Mai, I Vagliano, A Scherp Proceedings of the 26th conference on user modeling, adaptation and …, 2018 | 28 | 2018 |
| Open innovation in the big data era with the moving platform I Vagliano, F Günther, M Heinz, A Apaolaza, I Bienia, G Breitfuss, T Blume, ... IEEE MultiMedia 25 (3), 8-21, 2018 | 26 | 2018 |
| Machine learning models for predicting acute kidney injury: a systematic review and critical appraisal I Vagliano, NC Chesnaye, JH Leopold, KJ Jager, A Abu-Hanna, MC Schut Clinical Kidney Journal 15 (12), 2266-2280, 2022 | 18 | 2022 |
| An ontology-based contextual pre-filtering technique for recommender systems A Karpus, I Vagliano, K Goczyła, M Morisio 2016 Federated Conference on Computer Science and Information Systems …, 2016 | 17 | 2016 |
| Semantic annotation and classification in practice OR Rocha, I Vagliano, C Figueroa, F Cairo, G Futia, CA Licciardi, ... IT Professional 17 (2), 33-39, 2015 | 17 | 2015 |
| Content recommendation through semantic annotation of user reviews and linked data I Vagliano, D Monti, A Scherp, M Morisio Proceedings of the 9th Knowledge Capture Conference, 1-4, 2017 | 13 | 2017 |
| Serendipitous recommendations through ontology-based contextual pre-filtering A Karpus, I Vagliano, K Goczyła Beyond Databases, Architectures and Structures. Towards Efficient Solutions …, 2017 | 13 | 2017 |
| Redyal: A dynamic recommendation algorithm based on linked data I Vagliano, C Figueroa, OR Rocha, M Torchiano, CF Zucker, M Morisio RecSys 2016-3rd Workshop on New Trends in Content-Based Recommender Systems …, 2016 | 13 | 2016 |
| Can graph neural networks go" online"? an analysis of pretraining and inference L Galke, I Vagliano, A Scherp arXiv preprint arXiv:1905.06018, 2019 | 12 | 2019 |
| SemRevRec: A Recommender System based on User Reviews and Linked Data. I Vagliano, D Monti, M Morisio RecSys Posters, 2017 | 10 | 2017 |
| Lifelong learning on evolving graphs under the constraints of imbalanced classes and new classes L Galke, I Vagliano, B Franke, T Zielke, M Hoffmann, A Scherp Neural Networks 164, 156-176, 2023 | 9 | 2023 |
| Incremental training of graph neural networks on temporal graphs under distribution shift L Galke, I Vagliano, A Scherp Universität Ulm, 2020 | 9 | 2020 |
| Allied: A framework for executing linked data-based recommendation algorithms C Figueroa, I Vagliano, OR Rocha, M Torchiano, CF Zucker, JC Corrales, ... International Journal on Semantic Web and Information Systems (IJSWIS) 13 (4 …, 2017 | 8 | 2017 |
| Content recommendation through semantic annotation of user reviews and linked data-an extended technical report I Vagliano, D Monti, A Scherp, M Morisio arXiv preprint arXiv:1709.09973, 2017 | 8 | 2017 |
| Can we reliably automate clinical prognostic modelling? A retrospective cohort study for ICU triage prediction of in-hospital mortality of COVID-19 patients in the Netherlands I Vagliano, S Brinkman, A Abu-Hanna, MS Arbous, DA Dongelmans, ... International Journal of Medical Informatics 160, 104688, 2022 | 7 | 2022 |
| Analyzing the evolution of vocabulary terms and their impact on the LOD cloud M Abdel-Qader, A Scherp, I Vagliano European Semantic Web Conference, 1-16, 2018 | 7 | 2018 |
| Soft-prompt tuning to predict lung cancer using primary care free-text Dutch medical notes A Elfrink, I Vagliano, A Abu-Hanna, I Calixto International Conference on Artificial Intelligence in Medicine, 193-198, 2023 | 6 | 2023 |
| Executing, Comparing, and Reusing Linked-Data-Based Recommendation Algorithms with the Allied Framework C Figueroa, I Vagliano, OR Rocha, M Torchiano, CF Zucker, JC Corrales, ... Semantic Web science and real-world applications, 18-47, 2019 | 6 | 2019 |
| Using adversarial autoencoders for multi-modal automatic playlist continuation I Vagliano, L Galke, F Mai, A Scherp Proceedings of the ACM Recommender Systems Challenge 2018, 1-6, 2018 | 6 | 2018 |
Ansgar ScherpUniversity of Ulm, Germany在 ansgarscherp.net 的电子邮件经过验证
