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2017 | OriginalPaper | Buchkapitel

Authorship Attribution for Polish Texts Based on Part of Speech Tagging

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Abstract

Authorship attribution aims at identifying the author of an unseen text document based on text samples originating from different authors. In this paper we focus on authorship attribution of Polish texts using stylometric features based on part of speech (POS) tags. Polish language is characterized by high inflection level and in consequence over 1000 POS tags can be distinguished. This allows building a sufficiently large feature space by extracting POS information from documents and performing their classification with use of machine learning methods. We report results of experiments conducted with Weka workbench using combinations of the following features: POS tags, an approximation of their bigrams and simple document statistics.

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Metadaten
Titel
Authorship Attribution for Polish Texts Based on Part of Speech Tagging
verfasst von
Piotr Szwed
Copyright-Jahr
2017
DOI
https://doi.org/10.1007/978-3-319-58274-0_26

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