| A Survey on Knowledge Graphs: Representation, Acquisition and Applications S Ji, S Pan, E Cambria, P Marttinen, PS Yu IEEE Transactions on Neural Networks and Learning Systems (TNNLS) 33 (2 …, 2022 | 2109 | 2022 |
| BiERU: Bidirectional Emotional Recurrent Unit for Conversational Sentiment Analysis W Li, W Shao, S Ji, E Cambria Neurocomputing 467, 73-82, 2022 | 232 | 2022 |
| Suicidal Ideation Detection: A Review of Machine Learning Methods and Applications S Ji, S Pan, X Li, E Cambria, G Long, Z Huang IEEE Transactions on Computational Social Systems 8 (1), 214 - 226, 2021 | 215 | 2021 |
| Supervised learning for suicidal ideation detection in online user content S Ji, CP Yu, S Fung, S Pan, G Long Complexity 2018 (1), 6157249, 2018 | 203 | 2018 |
| Natural language processing applied to mental illness detection: a narrative review T Zhang, AM Schoene, S Ji, S Ananiadou NPJ digital medicine 5 (1), 1-13, 2022 | 191 | 2022 |
| MentalBERT: Publicly Available Pretrained Language Models for Mental Healthcare S Ji, T Zhang, L Ansari, J Fu, P Tiwari, E Cambria Proceedings of LREC, 7184--7190, 2022 | 187 | 2022 |
| Learning Private Neural Language Modeling with Attentive Aggregation S Ji, S Pan, G Long, X Li, J Jiang, Z Huang International Joint Conference on Neural Networks (IJCNN), 2019 | 160 | 2019 |
| Suicidal ideation and mental disorder detection with attentive relation networks S Ji, X Li, Z Huang, E Cambria Neural Computing and Applications 34 (13), 10309-10319, 2022 | 94 | 2022 |
| Towards Interpretable Mental Health Analysis with Large Language Models K Yang, S Ji, T Zhang, Q Xie, K Ziyan, S Ananiadou Proceedings of EMNLP, 6056–6077, 2023 | 88* | 2023 |
| Dynamic sampling and selective masking for communication-efficient federated learning S Ji, W Jiang, A Walid, X Li IEEE Intelligent Systems 37 (2), 27 - 34, 2022 | 75 | 2022 |
| Does the Magic of BERT Apply to Medical Code Assignment? A Quantitative Study S Ji, M Hölttä, P Marttinen Computers in Biology and Medicine 139, 2021 | 73 | 2021 |
| Decentralized knowledge acquisition for mobile internet applications J Jiang, S Ji, G Long World Wide Web 23, 2653–2669, 2020 | 46 | 2020 |
| Ensemble Hybrid Learning Methods for Automated Depression Detection L Ansari, S Ji, Q Chen, E Cambria IEEE Transactions on Computational Social Systems, 2022 | 44 | 2022 |
| Emerging trends in federated learning: From model fusion to federated x learning S Ji, Y Tan, T Saravirta, Z Yang, Y Liu, L Vasankari, S Pan, G Long, ... International Journal of Machine Learning and Cybernetics, 1-22, 2024 | 42 | 2024 |
| Sequential fusion of facial appearance and dynamics for depression recognition Q Chen, I Chaturvedi, S Ji, E Cambria Pattern Recognition Letters 150, 115-121, 2021 | 39 | 2021 |
| Automated Clinical Coding: What, Why, and Where We Are? H Dong, M Falis, W Whiteley, B Alex, J Matterson, S Ji, J Chen, H Wu npj Digital Medicine 5 (1), 1-8, 2022 | 37 | 2022 |
| Emotion fusion for mental illness detection from social media: A survey T Zhang, K Yang, S Ji, S Ananiadou Information Fusion 92, 231-246, 2023 | 33 | 2023 |
| Dilated Convolutional Attention Network for Medical Code Assignment from Clinical Text S Ji, E Cambria, P Marttinen Proceedings of the 3rd Clinical Natural Language Processing Workshop, 2020 | 32 | 2020 |
| Detecting suicidal ideation with data protection in online communities S Ji, G Long, S Pan, T Zhu, J Jiang, S Wang International Conference on Database Systems for Advanced Applications (DASFAA), 2019 | 29 | 2019 |
| Domain-specific Continued Pretraining of Language Models for Capturing Long Context in Mental Health S Ji, T Zhang, K Yang, S Ananiadou, E Cambria, J Tiedemann arXiv preprint arXiv:2304.10447, 2023 | 19 | 2023 |
Erik CambriaProfessor of Computing and Data Science, NTU Singapore在 ntu.edu.sg 的电子邮件经过验证
