BELDJOUDI BochraGAHAM SabrinaENCA/KHENNOUF Salah2024-07-102024-07-102024-07-10EL/2024https://dspace.univ-msila.dz/handle/123456789/43510The written word has always been a cornerstone of civilizations, essential for preserving and transmitting knowledge. Stylometry, at the intersection of linguistics and statistics, aims to identify a text's style, inherent to its author, as well as its era and genre. This technique analyzes anonymous texts to recognize their authors and applies to both ancient and modern texts. This work aims to identify the author of a specific Arabic text and test the robustness of an author recognition system. Features such as character N-Grams and classification techniques are used.StylometryAuthorship AttributionN-Grams CharacterMachine LearningThesis