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A Profile-Based Method for Authorship Verification

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Artificial Intelligence: Methods and Applications (SETN 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8445))

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Abstract

Authorship verification is one of the most challenging tasks in style-based text categorization. Given a set of documents, all by the same author, and another document of unknown authorship the question is whether or not the latter is also by that author. Recently, in the framework of the PAN-2013 evaluation lab, a competition in authorship verification was organized and the vast majority of submitted approaches, including the best performing models, followed the instance-based paradigm where each text sample by one author is treated separately. In this paper, we show that the profile-based paradigm (where all samples by one author are treated cumulatively) can be very effective surpassing the performance of PAN-2013 winners without using any information from external sources. The proposed approach is fully-trainable and we demonstrate an appropriate tuning of parameter settings for PAN-2013 corpora achieving accurate answers especially when the cost of false negatives is high.

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Author information

Authors and Affiliations

  1. Dept. of Information and Communication Systems Eng., University of the Aegean, 83200, Karlovassi, Greece

    Nektaria Potha & Efstathios Stamatatos

Authors
  1. Nektaria Potha
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  2. Efstathios Stamatatos
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Editor information

Editors and Affiliations

  1. Department of Computer Science, University of Ioannina, GR 45110, Ioannina, Greece

    Aristidis Likas

  2. Department of Computer Science, University of Ioannina, P.O. Box 1186, 45110, Ioannina, Greece

    Konstantinos Blekas

  3. Hellenic Open University, GR 26335, Peribola, Patras, Greece

    Dimitris Kalles

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Potha, N., Stamatatos, E. (2014). A Profile-Based Method for Authorship Verification. In: Likas, A., Blekas, K., Kalles, D. (eds) Artificial Intelligence: Methods and Applications. SETN 2014. Lecture Notes in Computer Science(), vol 8445. Springer, Cham. https://doi.org/10.1007/978-3-319-07064-3_25

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  • DOI: https://doi.org/10.1007/978-3-319-07064-3_25

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-07063-6

  • Online ISBN: 978-3-319-07064-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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