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

Abstract : 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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https://hal.archives-ouvertes.fr/hal-01527780
Contributor : Francesca Frontini <>
Submitted on : Thursday, May 25, 2017 - 1:44:53 PM
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  • HAL Id : hal-01527780, version 1

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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, Alliance of Digital Humanities, 2017, Göttingen Dialog in Digital Humanities 2015, 11 (2). ⟨hal-01527780⟩

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