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Authorship Identification Using Random Projections

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Artificial Intelligence and Algorithms in Intelligent Systems (CSOC2018 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 764))

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Abstract

The paper describes the results of experiments in applying the Random Projection (RP) method for authorship identification of online texts. We propose using RP for feature dimensionality reduction to low-dimensional feature subspace combined with probability density function (PDF) estimation for identification of the features of each author. In our experiments, we use the dataset of Internet comments posted on a web news site in Lithuanian language, and we have achieved 92% accuracy of author identification.

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Author information

Authors and Affiliations

  1. Department of Software Engineering, Kaunas University of Technology, Kaunas, Lithuania

    Robertas Damaševičius

  2. Faculty of Informatics, Vytautas Magnus University, Kaunas, Lithuania

    Jurgita Kapočiūtė-Dzikienė

  3. Institute of Mathematics, Silesian University of Technology, Gliwice, Poland

    Marcin Woźniak

Authors
  1. Robertas Damaševičius
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  2. Jurgita Kapočiūtė-Dzikienė
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  3. Marcin Woźniak
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Corresponding author

Correspondence to Robertas Damaševičius .

Editor information

Editors and Affiliations

  1. Faculty of Applied Informatics, Tomas Bata University in Zlín, Zlín, Czech Republic

    Radek Silhavy

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Damaševičius, R., Kapočiūtė-Dzikienė, J., Woźniak, M. (2019). Authorship Identification Using Random Projections. In: Silhavy, R. (eds) Artificial Intelligence and Algorithms in Intelligent Systems. CSOC2018 2018. Advances in Intelligent Systems and Computing, vol 764. Springer, Cham. https://doi.org/10.1007/978-3-319-91189-2_6

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