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2017 | OriginalPaper | Buchkapitel

Stylometric Features for Authorship Attribution of Polish Texts

verfasst von : Piotr Szwed

Erschienen in: Artificial Intelligence and Soft Computing

Verlag: Springer International Publishing

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Abstract

Authorship attribution aims at distinguishing texts written by different authors using text features representing their styles. In this paper we investigate stylometric features for the Polish language based on Part of Speech (POS) tagging (including POS bigrams) and function words. Due to high inflection level of Polish language the feature space tends to be very large. This in particular concerns POS n-grams. Focusing on POS bigrams, we propose their simplified representation allowing to keep the feature space compact. We report experiments, in which authorship attribution was conducted for varying in lengths documents, with use of classifiers from the Weka library. We evaluate classification results for combinations of the following features: POS tags, POS bigrams, function words and simple document statistics. Experiments indicate that the developed features provide good classification performance.

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Vorheriges Kapitel Improvement of the Validity Index for Determination of an Appropriate Data Partitioning

Nächstes Kapitel Handwriting Recognition with Extraction of Letter Fragments

https://sites.google.com/site/computationalstylistics/.

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Titel: Stylometric Features for Authorship Attribution of Polish Texts
verfasst von: Piotr Szwed
Verlag: Springer International Publishing
Buch: Artificial Intelligence and Soft Computing
Print ISBN: 978-3-319-59059-2

Electronic ISBN: 978-3-319-59060-8

Copyright-Jahr: 2017
DOI: https://doi.org/10.1007/978-3-319-59060-8_17

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