• Refine your search:
  • 
    Keyword
  • 
    Creator / Publisher:
    
    • Abdelali, Ahmed (7)
    • Darwish, Kareem (7)
    • Mubarak, Hamdy (7)
    • Samih, Younes (5)
    • Attia, Mohammed (2)
    • Eldesouki, Mohamed (2)
    • Hassan, Sabit (2)
    • Laura, Kallmeyer (1)
    • Rashed, Ammar (1)
    • Shoukry, Shimaa (1)
    •   more
  • 
    Year
  • 
    Medium
  • 
    Type
  • 
    BLLDB-Access:
    • free (7)
    • subject to license (0)

Search in the Catalogues and Directories

All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 7 of 7 1 Pre-Training BERT on Arabic Tweets: Practical Considerations ... Abdelali, Ahmed; Hassan, Sabit; Mubarak, Hamdy. - : arXiv, 2021 BASE Show details 2 Arabic Offensive Language on Twitter: Analysis and Experiments ... Mubarak, Hamdy; Rashed, Ammar; Darwish, Kareem. - : arXiv, 2020 BASE Show details 3 Arabic Dialect Identification in the Wild ... Abdelali, Ahmed; Mubarak, Hamdy; Samih, Younes; Hassan, Sabit; Darwish, Kareem. - : arXiv, 2020 Abstract: We present QADI, an automatically collected dataset of tweets belonging to a wide range of country-level Arabic dialects -covering 18 different countries in the Middle East and North Africa region. Our method for building this dataset relies on applying multiple filters to identify users who belong to different countries based on their account descriptions and to eliminate tweets that are either written in Modern Standard Arabic or contain inappropriate language. The resultant dataset contains 540k tweets from 2,525 users who are evenly distributed across 18 Arab countries. Using intrinsic evaluation, we show that the labels of a set of randomly selected tweets are 91.5% accurate. For extrinsic evaluation, we are able to build effective country-level dialect identification on tweets with a macro-averaged F1-score of 60.6% across 18 classes. ... : 13 pages, 7 figures, 4 tables ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/2005.06557 https://dx.doi.org/10.48550/arxiv.2005.06557 BASE Hide details 4 Arabic Curriculum Analysis ... The 28th International Conference on Computational Linguistics 2020; Abdelali, Ahmed; Darwish, Kareem. - : Underline Science Inc., 2020 BASE Show details 5 Arabic Diacritic Recovery Using a Feature-Rich biLSTM Model ... Darwish, Kareem; Abdelali, Ahmed; Mubarak, Hamdy. - : arXiv, 2020 BASE Show details 6 Diacritization of Maghrebi Arabic Sub-Dialects ... Abdelali, Ahmed; Attia, Mohammed; Samih, Younes. - : arXiv, 2018 BASE Show details 7 Arabic Multi-Dialect Segmentation: bi-LSTM-CRF vs. SVM ... Eldesouki, Mohamed; Samih, Younes; Abdelali, Ahmed. - : arXiv, 2017 BASE Show details

Mobile view All Catalogues UB Frankfurt Linguistik 0 IDS Mannheim 0 OLC Linguistik 0 UB Frankfurt Retrokatalog 0 DNB Subject Category Language 0 Institut für Empirische Sprachwissenschaft 0 Leibniz-Centre General Linguistics (ZAS) 0 Bibliographies BLLDB 0 BDSL 0 IDS Bibliografie zur deutschen Grammatik 0 IDS Bibliografie zur Gesprächsforschung 0 IDS Konnektoren im Deutschen 0 IDS Präpositionen im Deutschen 0 IDS OBELEX meta 0 MPI-SHH Linguistics Collection 0 MPI for Psycholinguistics 0 Linked Open Data catalogues Annohub 0 Online resources Link directory 0 Journal directory 0 Database directory 0 Dictionary directory 0 Open access documents BASE 7 Linguistik-Repository 0 IDS Publikationsserver 0 Online dissertations 0 Language Description Heritage 0