| Table Search Using a Deep Contextualized Language Model Z Chen, M Trabelsi, J Heflin, Y Xu, BD Davison Proceedings of 43rd International ACM SIGIR Conference on Research and …, 2020 | 74 | 2020 |
| StruBERT: Structure-aware BERT for Table Search and Matching M Trabelsi, Z Chen, S Zhang, BD Davison, J Heflin Proceedings of the Web Conference (WWW 2022), 2022 | 42 | 2022 |
| Neural ranking models for document retrieval M Trabelsi, Z Chen, BD Davison, J Heflin Information Retrieval Journal, 2021 | 38 | 2021 |
| Improved table retrieval using multiple context embeddings for attributes M Trabelsi, BD Davison, J Heflin 2019 IEEE international conference on big data (Big Data), 1238-1244, 2019 | 24 | 2019 |
| LogGPT: Log Anomaly Detection via GPT X Han, S Yuan, M Trabelsi 2023 IEEE International Conference on Big Data (Big Data), 2023 | 19 | 2023 |
| Robust fuzzy clustering for multiple instance regression M Trabelsi, H Frigui Pattern Recognition 90, 424-435, 2019 | 15 | 2019 |
| DAME: Domain Adaptation for Matching Entities M Trabelsi, J Heflin, J Cao Proceedings of the 15th ACM International Conference on Web Search and Data …, 2022 | 14 | 2022 |
| SeLaB: Semantic Labeling with BERT M Trabelsi, J Cao, J Heflin 2021 International Joint Conference on Neural Networks (IJCNN), 2021 | 14 | 2021 |
| Semantic Labeling Using a Deep Contextualized Language Model M Trabelsi, J Cao, J Heflin arXiv preprint arXiv:2010.16037, 2020 | 13 | 2020 |
| A Hybrid Deep Model for Learning to Rank Data Tables M Trabelsi, Z Chen, BD Davison, J Heflin 2020 IEEE International Conference on Big Data (Big Data), 2020 | 9 | 2020 |
| Relational Graph Embeddings for Table Retrieval M Trabelsi, Z Chen, BD Davison, J Heflin 2020 IEEE International Conference on Big Data (Big Data), 2020 | 7 | 2020 |
| MGNETS: Multi-Graph Neural Networks for Table Search Z Chen, M Trabelsi, J Heflin, D Yin, BD Davison Proceedings of the 30th ACM International Conference on Information and …, 2021 | 6 | 2021 |
| Fuzzy and possibilistic clustering for multiple instance linear regression M Trabelsi, H Frigui 2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 1-7, 2018 | 5 | 2018 |
| Towards Knowledge Acquisition of Metadata on AI Progress Z Chen, M Trabelsi, BD Davison, J Heflin ISWC (Posters & Demos) 2020, 2020 | 3 | 2020 |
| Absformer: Transformer-based Model for Unsupervised Multi-Document Abstractive Summarization M Trabelsi, H Uzunalioglu Document Analysis and Recognition – ICDAR 2023 Workshops, 2023 | 2 | 2023 |
| Comparison of several single and multiple instance learning methods for detecting buried explosive objects using gpr data A Karem, M Trabelsi, M Moalla, H Frigui Detection and sensing of mines, explosive objects, and obscured targets …, 2018 | 2 | 2018 |
| Time Series Language Model for Descriptive Caption Generation M Trabelsi, A Boyd, J Cao, H Uzunalioglu arXiv preprint arXiv:2501.01832, 2025 | | 2025 |
| Increasing Interpretability of Neural Networks By Approximating Human Visual Saliency A Boyd, M Trabelsi, H Uzunalioglu, D Kushnir arXiv preprint arXiv:2410.16115, 2024 | | 2024 |
| Leveraging Dataset Content in Neural Models for Search and Curation M Trabelsi Lehigh University, 2022 | | 2022 |
Jeff HeflinComputer Science and Engineering, Lehigh UniversityAdresse e-mail validée de cse.lehigh.edu