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# Mohamed Eldesouki

2 paper cards in Mova's library · 2017

Mohamed Eldesouki wrote 2 of the papers Mova reads, in 2017, most of them on [Treebanks](https://md.mova.elamur.ai/free/en/docs/papers/topics/treebanks/); often with [Ahmed Abdelali](https://md.mova.elamur.ai/free/en/docs/papers/authors/ahmed-abdelali/), [Hamdy Mubarak](https://md.mova.elamur.ai/free/en/docs/papers/authors/hamdy-mubarak/), [Kareem Darwish](https://md.mova.elamur.ai/free/en/docs/papers/authors/kareem-darwish/).

[OpenAlex](https://openalex.org/A5033221342) · [ORCID](https://orcid.org/0009-0009-6662-5883) · [**h-index 6**](https://openalex.org/authors/A5033221342) · [198 citations](https://openalex.org/authors/A5033221342) · [88 works](https://openalex.org/works?filter=author.id:A5033221342) — openalex, 2026-10-18

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Mohamed+Eldesouki) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Mohamed+Eldesouki) · [dblp](https://dblp.org/search?q=Mohamed+Eldesouki) · [ACL Anthology](https://aclanthology.org/search/?q=Mohamed+Eldesouki) · [ORCID](https://orcid.org/orcid-search/search?searchQuery=Mohamed+Eldesouki)

Topics: [Treebanks](https://md.mova.elamur.ai/free/en/docs/papers/topics/treebanks/) 1

## Papers

1. **[A Neural Architecture for Dialectal Arabic Segmentation](https://md.mova.elamur.ai/free/en/docs/papers/aclbulk-2017-samih-neural-architecture-dialectal-arabic-segmentation/)** *(2017)* Egyptian Arabic in tweets has no standard spelling and few annotated resources, and the clitics attached to its verbs are missed by MSA tools.
2. **[Arabic Multi-Dialect Segmentation: bi-LSTM-CRF vs. SVM](https://md.mova.elamur.ai/free/en/docs/papers/langstream-2017-eldesouki-arabic-multi-dialect-segmentation-bi/)** *(2017)* The paper segments four Arabic dialects (Egyptian, Levantine, Gulf, Maghrebi) from raw Twitter text. Only about 350 manually segmented tweets per dialect are used for training, with 5-fold cross-validation and a 70/10/20 split. Two approaches are compared. An SVM ranker generates all segmentations of a word from a…

## Co-authors (7)

- [Ahmed Abdelali](https://md.mova.elamur.ai/free/en/docs/papers/authors/ahmed-abdelali/) ×2
- [Hamdy Mubarak](https://md.mova.elamur.ai/free/en/docs/papers/authors/hamdy-mubarak/) ×2
- [Kareem Darwish](https://md.mova.elamur.ai/free/en/docs/papers/authors/kareem-darwish/) ×2
- [Mohammed Attia](https://md.mova.elamur.ai/free/en/docs/papers/authors/mohammed-attia/) ×2
- [Younes Samih](https://md.mova.elamur.ai/free/en/docs/papers/authors/younes-samih/) ×2
- Kallmeyer Laura
- Laura Kallmeyer
- [← previous Mohamed Al-Badrashiny](https://md.mova.elamur.ai/free/en/docs/papers/authors/mohamed-al-badrashiny/)
- [next → Mohamed Maamouri](https://md.mova.elamur.ai/free/en/docs/papers/authors/mohamed-maamouri/)
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