Maayan Zhitomirsky-Geffet
Maayan Zhitomirsky-Geffet wrote 3 of the papers Mova reads, in 2023–2026, most of them on Named entity recognition; often with Avshalom Elmalech, Omri Suissa, Binyamin Katzoff.
Topics: Named entity recognition 1
Papers
- Domain-Aware Error Correction for Citation NER in Medieval Hebrew Responsa (2026)
The task is citation NER in medieval Hebrew Responsa: each token of a citation gets a role (book name, author, reference number, reference word, and so on, or outside). - Toward a Period-Specific Optimized Neural Network for OCR Error Correction of Historical Hebrew Texts (2023)
The full version of the authors' work on Hebrew OCR post-correction. They align 70% of hand-corrected JPress newspaper articles with their OCR output (Needleman–Wunsch) to learn character-level, period-specific confusions — the commonest being ח→ה (about 8%), ד→ר (5%), ג→נ, ב→כ, ם→ס, ח→ת, ו↔י — and inject them into… - Optimizing the Neural Network Training for OCR Error Correction of Historical Hebrew Texts (2023)
OCR of historical Hebrew newspapers (the JPress collection) is noisy, and neural post-correctors need large hand-corrected sets.
Co-authors (6)
- Avshalom Elmalech ×2
- Omri Suissa ×2
- Binyamin Katzoff
- Jonathan Schler
- Nati Ben-Gigi
- Shmuel LIebeskind
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