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Authorship Attribution System

  • Oleksandr Marchenko
  • Anatoly Anisimov
  • Andrii Nykonenko
  • Tetiana Rossada
  • Egor Melnikov
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10260)

Abstract

A new effective system for identification and verification of text authorship has been developed. The system is created on the basis of machine learning. The originality of the model is caused by a suggested unique profile of the author’s style features. Together with the use of the Support Vector Machine method, this allows us to achieve the high accuracy of the authorship detection. Proposed method allows the system to learn styles for a large number of authors using small amount of data in a training set.

Keywords

Machine learning Support Vector Machine Authorship detection 

Notes

Acknowledgments

The authors of the article are grateful to Phase One: Karma LTD company, especially to the Unplag team for the support in research and considerable assistance in the development, testing and implementation of the authorship attribution method.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Oleksandr Marchenko
    • 1
  • Anatoly Anisimov
    • 1
  • Andrii Nykonenko
    • 2
  • Tetiana Rossada
    • 1
  • Egor Melnikov
    • 3
  1. 1.Taras Shevchenko National University of KyivKievUkraine
  2. 2.International Research and Training Center for IT and SystemsKyivUkraine
  3. 3.Phase One: Karma LTDLondonUK

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