Establishing Relevance of Characteristic Features for Authorship Attribution with ANN

  • Urszula Stańczyk
Conference paper

DOI: 10.1007/978-3-642-40173-2_1

Part of the Lecture Notes in Computer Science book series (LNCS, volume 8056)
Cite this paper as:
Stańczyk U. (2013) Establishing Relevance of Characteristic Features for Authorship Attribution with ANN. In: Decker H., Lhotská L., Link S., Basl J., Tjoa A.M. (eds) Database and Expert Systems Applications. DEXA 2013. Lecture Notes in Computer Science, vol 8056. Springer, Berlin, Heidelberg

Abstract

Authorship attribution is perceived as a task of the paramount importance within stylometric analysis of texts. It encompasses author characterisation and comparison, and by observation and recognition of patterns in individual stylistic traits enables confirmation or rejection of authorship claims. Stylometry requires reliable textual descriptors and knowledge about their relevance for the case under study. One of the possible ways to evaluate this relevance is to employ a feature selection and reduction algorithm in the wrapper model. The paper presents research on such procedure applied to artificial neural networks used to categorise literary texts with respect to their authors, with importance of attributes discovered through sequential backward search.

Keywords

Stylometry Authorship Attribution Characteristic Feature Feature Relevance Feature Selection Sequential Backward Search 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Urszula Stańczyk
    • 1
  1. 1.Institute of InformaticsSilesian University of TechnologyGliwicePoland

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