| Compression versus traditional machine learning classifiers to detect code-switching in varieties and dialects: Arabic as a case study T Tarmom, W Teahan, E Atwell, MA Alsalka Natural Language Engineering 26 (6), 663-676, 2020 | 8 | 2020 |
| Deep learning vs compression-based vs traditional machine learning classifiers to detect Hadith authenticity T Tarmom, E Atwell, M Alsalka Annual International Conference on Information Management and Big Data, 206-222, 2021 | 7 | 2021 |
| Non-authentic Hadith corpus: Design and methodology T Tarmom, E Atwell, M Alsalka Proceedings of IMAN 2019, 2019 | 7 | 2019 |
| Compression vs Traditional Machine Learning Classifiers to Detect Code-switching in Varieties and Dialects: Arabic as a Case Study T Tarmom, W Teahan, E Atwell, M Alsalka Journal of Natural Language Engineering, 2018 | 2 | 2018 |
| Automatic Hadith Segmentation using PPM Compression T Tarmom, E Atwell, MA Alsalka Proceedings of the 17th International Conference on Natural Language …, 2020 | 1 | 2020 |
| Compression versus machine learning for classifying modern Arabic code-switching in social media and classical Arabic Hadith TA Tarmom University of Leeds, 2022 | | 2022 |
| Code-Switching in Arabic Dialect Corpora: Compression vs Traditional Machine Learning Classifiers to Detect Code-switching T Tarmom, W Teahan, E Atwell, M Alsalka This conference does not have proceedings, 2019 | | 2019 |
| Deep Learning vs Compression-Based vs Traditional Machine Learning Classifiers to Classify Arabic Hadith Text T Tarmom, E Atwell, M Alsalka | | |
