Authorship Attribution of Specific Arabic Texts using Character N-gram and Classification Techniques
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Date
2024-07-10
Journal Title
Journal ISSN
Volume Title
Publisher
UNIVERSITY OF MOHAMED BOUDIAF-M’SILA
Abstract
The 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.
Description
Keywords
Stylometry, Authorship Attribution, N-Grams Character, Machine Learning