Abstract: In the article authorshi p identification problem in the case of the limited set of alternatives is described. Generalized technique for authorshi p identification and for authors’ style model generating in the form of studied classifier is given. Also results of authorshi p identification experiments for corpuses of Russian literary texts and short messages are represented.
Keywords: authorshi p identification, classifire, artifical neural networks, support vector machine, smoothing
Authors and copyright holders:
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For citation:
Romanov A. S., Shelupanov A. A., Bondarchuk S. S. Generalized authorship identification technique. Doklady Tomskogo gosudarstvennogo universiteta sistem upravleniya i radioelektroniki, 2010, no. 1(21), – p. 1. pp. 108–112.
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