תקציר
The main sources of information regarding ancient Mesopotamian history and culture are clay cuneiform tablets. Many of these tablets are damaged, leading to missing information. Currently, the missing text is manually reconstructed by experts. We investigate the possibility of assisting scholars, by modeling the language using recurrent neural networks and automatically completing the breaks in ancient Akkadian texts from Achaemenid period Babylonia.
| שפה מקורית | אנגלית |
|---|---|
| עמודים (מ-עד) | 22743-22751 |
| מספר עמודים | 9 |
| כתב עת | Proceedings of the National Academy of Sciences of the United States of America |
| כרך | 117 |
| מספר גיליון | 37 |
| מזהי עצם דיגיטלי (DOIs) | |
| סטטוס פרסום | פורסם - 15 ספט׳ 2020 |