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Article Dans Une Revue Digital Humanities Quarterly Année : 2017

Mining for characterising patterns in literature using correspondence analysis: an experiment on French novels

Résumé

This paper presents and describes a bottom-up methodology for the detection of stylistic traits in the syntax of literary texts. The extraction of syntactic patterns is performed blindly by a sequential pattern mining algorithm, while the identification of significant and interesting features is performed at a later stage by using correspondence analysis and by ranking patterns by contribution.
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Dates et versions

hal-01527780 , version 1 (25-05-2017)

Licence

Paternité - Pas d'utilisation commerciale - Pas de modification

Identifiants

  • HAL Id : hal-01527780 , version 1

Citer

Francesca Frontini, Mohamed Amine Boukhaled, Jean-Gabriel Ganascia. Mining for characterising patterns in literature using correspondence analysis: an experiment on French novels. Digital Humanities Quarterly, 2017, Göttingen Dialog in Digital Humanities 2015, 11 (2). ⟨hal-01527780⟩
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