Authorship Attribution of Specific Arabic Texts using Character N-gram and Classification Techniques

dc.contributor.authorBELDJOUDI Bochra
dc.contributor.authorGAHAM Sabrina
dc.contributor.authorENC/ KHENNOUF Salah
dc.date.accessioned2024-07-14T10:01:14Z
dc.date.available2024-07-14T10:01:14Z
dc.date.issued2024-07-14
dc.description.abstractEN 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. FR La parole écrite a toujours été une pierre angulaire des civilisations, essentielle pour préserver et transmettre le savoir. La stylométrie, à l'intersection de la linguistique et des statistiques, vise à identifier le style d'un texte, propre à son auteur, ainsi que son époque et son genre. Cette technique analyse les textes anonymes pour en reconnaître les auteurs et s'applique aux textes anciens et modernes. Ce travail vise à identifier l'auteur d'un texte arabe spécifique et à tester la robustesse d'un système de reconnaissance d'auteur. Les caractéristiques comme les character N-Grams et les techniques de classification sont utilisées.
dc.identifier.urihttps://dspace.univ-msila.dz/handle/123456789/43690
dc.language.isoen
dc.publisherUniversity of M'sila
dc.relation.ispartofseries2024
dc.subjectStylometry
dc.subjectAuthorship Attribution
dc.subjectN-Grams Character
dc.subjectMachine Learning.
dc.titleAuthorship Attribution of Specific Arabic Texts using Character N-gram and Classification Techniques
dc.typeThesis

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