Abstract
The paper proposes an original methodology of authorship attribution based on the deviations from Zipf distribution and statistical data obtained with the help of a concordance program and computations performed in a table processor. The methodology involves finding distances between input texts and a reference text basing on deviations of stop-words frequencies. The results that have been achieved prove that the proposed methodology allows performing efficient authorship attribution and that it can be used in the educational process to develop student skills and competencies pertaining to natural language processing.
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