TY - GEN

T1 - Spectral Profiling of Writing Process

AU - Kizhaeva, Natalia

AU - Volkovich, Zeev

AU - Granichin, Oleg

AU - Granichina, Olga

AU - Kiyaev, Vladimir

PY - 2017

Y1 - 2017

N2 - This paper discusses a novel methodology for dynamic modeling of writing process. Sequent sub-documents of a given document are described through occurrences of the suitably selected N-grams. The Mean Dependence similarity measures the association between a present sub-document and numerous preceding ones and transforms a document into a time series, which is supposed to be weak stationary if the document is created using the same writing style. A periodogram of this signal estimates its Power Spectral Density providing a spectral attribute of the style. Numerical experiments demonstrate high ability of the proposed method in authorship identification and the reveal of writing style evolution.

AB - This paper discusses a novel methodology for dynamic modeling of writing process. Sequent sub-documents of a given document are described through occurrences of the suitably selected N-grams. The Mean Dependence similarity measures the association between a present sub-document and numerous preceding ones and transforms a document into a time series, which is supposed to be weak stationary if the document is created using the same writing style. A periodogram of this signal estimates its Power Spectral Density providing a spectral attribute of the style. Numerical experiments demonstrate high ability of the proposed method in authorship identification and the reveal of writing style evolution.

KW - Writing style

KW - Authorship Attribution

KW - Spectral attributing

M3 - статья в сборнике материалов конференции

SP - 2063

EP - 2068

BT - 2017 IEEE CONFERENCE ON CONTROL TECHNOLOGY AND APPLICATIONS (CCTA 2017)

PB - IEEE Canada

Y2 - 27 August 2017 through 30 August 2017

ER -