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Spectral Profiling of Writing Process. / Kizhaeva, Natalia; Volkovich, Zeev; Granichin, Oleg; Granichina, Olga; Kiyaev, Vladimir.

2017 IEEE CONFERENCE ON CONTROL TECHNOLOGY AND APPLICATIONS (CCTA 2017). IEEE Canada, 2017. p. 2063-2068.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Research › peer-review

Harvard

Kizhaeva, N, Volkovich, Z, Granichin, O, Granichina, O & Kiyaev, V 2017, Spectral Profiling of Writing Process. in 2017 IEEE CONFERENCE ON CONTROL TECHNOLOGY AND APPLICATIONS (CCTA 2017). IEEE Canada, pp. 2063-2068, 1st Annual IEEE Conference on Control Technology and Applications, United States, 27/08/17.

APA

Kizhaeva, N., Volkovich, Z., Granichin, O., Granichina, O., & Kiyaev, V. (2017). Spectral Profiling of Writing Process. In 2017 IEEE CONFERENCE ON CONTROL TECHNOLOGY AND APPLICATIONS (CCTA 2017) (pp. 2063-2068). IEEE Canada.

Vancouver

Kizhaeva N, Volkovich Z, Granichin O, Granichina O, Kiyaev V. Spectral Profiling of Writing Process. In 2017 IEEE CONFERENCE ON CONTROL TECHNOLOGY AND APPLICATIONS (CCTA 2017). IEEE Canada. 2017. p. 2063-2068

Author

Kizhaeva, Natalia ; Volkovich, Zeev ; Granichin, Oleg ; Granichina, Olga ; Kiyaev, Vladimir. / Spectral Profiling of Writing Process. 2017 IEEE CONFERENCE ON CONTROL TECHNOLOGY AND APPLICATIONS (CCTA 2017). IEEE Canada, 2017. pp. 2063-2068

BibTeX

@inproceedings{2ca9fecc13b84546ba1c82a48fe946ea,
title = "Spectral Profiling of Writing Process",
abstract = "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.",
keywords = "Writing style, Authorship Attribution, Spectral attributing",
author = "Natalia Kizhaeva and Zeev Volkovich and Oleg Granichin and Olga Granichina and Vladimir Kiyaev",
year = "2017",
language = "Английский",
pages = "2063--2068",
booktitle = "2017 IEEE CONFERENCE ON CONTROL TECHNOLOGY AND APPLICATIONS (CCTA 2017)",
publisher = "IEEE Canada",
address = "Канада",
note = "null ; Conference date: 27-08-2017 Through 30-08-2017",

}

RIS

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 -

ID: 32479602