On Unsupervised and Supervised Discretisation in Mining Stylometric Features

Urszula Stańczyk

doi:10.1007/978-3-030-31964-9_15

On Unsupervised and Supervised Discretisation in Mining Stylometric Features

Urszula Stańczyk

Katedra Grafiki, Wizji Komputerowej i Systemów Cyfrowych (RAU/RAU6)

Wyniki badań: Rozdział w książce/raport/materiał konferencyjny › Wkład w konferencję › recenzja

4 Cytowania z bazy Scopus

Abstrakt

Writing styles can be described by stylometric features. They are quantitative in nature, often continuous, which either limits techniques used in mining to those capable of calculations on this form, or adds discretisation to initial pre-processing of data. The paper describes research on unsupervised and supervised discretisation applied in the stylometric domain for the task of authorship attribution. The recognition of authorship is executed as classification performed by chosen inducers capable of operating on both continuous and categorical attributes.

Język oryginału	angielski
Tytuł publikacji goszczącej	Man-Machine Interactions 6 - 6th International Conference on Man-Machine Interactions, ICMMI 2019
Redaktorzy	Aleksandra Gruca, Sebastian Deorowicz, Katarzyna Harezlak, Agnieszka Piotrowska, Tadeusz Czachórski
Wydawca	Springer
Strony	156-166
Liczba stron	11
ISBN (drukowany)	9783030319632
Identyfikatory DOI	https://doi.org/10.1007/978-3-030-31964-9_15
Status publikacji	Opublikowano - 2020
Wydarzenie	6th International Conference on Man-Machine Interactions, ICMMI 2019 - Cracow, Polska Czas trwania: 2 paź 2019 → 3 paź 2019

Seria publikacji

Nazwa	Advances in Intelligent Systems and Computing
Tom	1061
ISSN (drukowany)	2194-5357
ISSN (elektroniczny)	2194-5365

Konferencja

Konferencja	6th International Conference on Man-Machine Interactions, ICMMI 2019
Kraj/Terytorium	Polska
Miejscowość	Cracow
Okres	2/10/19 → 3/10/19

Obszary tematyczne ASJC Scopus

Inżynieria sterowania i systemów
Informatyka ogólna

Uzyskaj dostęp do dokumentu

10.1007/978-3-030-31964-9_15

Inne pliki i linki

Link do publikacji w Scopus

Cytowanie

Stańczyk, U. (2020). On Unsupervised and Supervised Discretisation in Mining Stylometric Features. W A. Gruca, S. Deorowicz, K. Harezlak, A. Piotrowska, & T. Czachórski (Red.), Man-Machine Interactions 6 - 6th International Conference on Man-Machine Interactions, ICMMI 2019 (str. 156-166). (Advances in Intelligent Systems and Computing; Tom 1061). Springer. https://doi.org/10.1007/978-3-030-31964-9_15

Stańczyk, Urszula. / On Unsupervised and Supervised Discretisation in Mining Stylometric Features. Man-Machine Interactions 6 - 6th International Conference on Man-Machine Interactions, ICMMI 2019. redaktor / Aleksandra Gruca ; Sebastian Deorowicz ; Katarzyna Harezlak ; Agnieszka Piotrowska ; Tadeusz Czachórski. Springer, 2020. str. 156-166 (Advances in Intelligent Systems and Computing).

@inproceedings{f9c73766bcb147be9b259b7ed99caf90,

title = "On Unsupervised and Supervised Discretisation in Mining Stylometric Features",

abstract = "Writing styles can be described by stylometric features. They are quantitative in nature, often continuous, which either limits techniques used in mining to those capable of calculations on this form, or adds discretisation to initial pre-processing of data. The paper describes research on unsupervised and supervised discretisation applied in the stylometric domain for the task of authorship attribution. The recognition of authorship is executed as classification performed by chosen inducers capable of operating on both continuous and categorical attributes.",

keywords = "Authorship attribution, Feature, Stylometry, Supervised discretisation, Unsupervised discretisation",

author = "Urszula Sta{\'n}czyk",

note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; 6th International Conference on Man-Machine Interactions, ICMMI 2019 ; Conference date: 02-10-2019 Through 03-10-2019",

year = "2020",

doi = "10.1007/978-3-030-31964-9\_15",

language = "English",

isbn = "9783030319632",

series = "Advances in Intelligent Systems and Computing",

publisher = "Springer",

pages = "156--166",

editor = "Aleksandra Gruca and Sebastian Deorowicz and Katarzyna Harezlak and Agnieszka Piotrowska and Tadeusz Czach{\'o}rski",

booktitle = "Man-Machine Interactions 6 - 6th International Conference on Man-Machine Interactions, ICMMI 2019",

address = "Germany",

}

Stańczyk, U 2020, On Unsupervised and Supervised Discretisation in Mining Stylometric Features. w A Gruca, S Deorowicz, K Harezlak, A Piotrowska & T Czachórski (red), Man-Machine Interactions 6 - 6th International Conference on Man-Machine Interactions, ICMMI 2019. Advances in Intelligent Systems and Computing, tom 1061, Springer, str. 156-166, 6th International Conference on Man-Machine Interactions, ICMMI 2019, Cracow, Polska, 2/10/19. https://doi.org/10.1007/978-3-030-31964-9_15

On Unsupervised and Supervised Discretisation in Mining Stylometric Features. / Stańczyk, Urszula.
Man-Machine Interactions 6 - 6th International Conference on Man-Machine Interactions, ICMMI 2019. red. / Aleksandra Gruca; Sebastian Deorowicz; Katarzyna Harezlak; Agnieszka Piotrowska; Tadeusz Czachórski. Springer, 2020. str. 156-166 (Advances in Intelligent Systems and Computing; Tom 1061).

Wyniki badań: Rozdział w książce/raport/materiał konferencyjny › Wkład w konferencję › recenzja

TY - GEN

T1 - On Unsupervised and Supervised Discretisation in Mining Stylometric Features

AU - Stańczyk, Urszula

PY - 2020

Y1 - 2020

N2 - Writing styles can be described by stylometric features. They are quantitative in nature, often continuous, which either limits techniques used in mining to those capable of calculations on this form, or adds discretisation to initial pre-processing of data. The paper describes research on unsupervised and supervised discretisation applied in the stylometric domain for the task of authorship attribution. The recognition of authorship is executed as classification performed by chosen inducers capable of operating on both continuous and categorical attributes.

AB - Writing styles can be described by stylometric features. They are quantitative in nature, often continuous, which either limits techniques used in mining to those capable of calculations on this form, or adds discretisation to initial pre-processing of data. The paper describes research on unsupervised and supervised discretisation applied in the stylometric domain for the task of authorship attribution. The recognition of authorship is executed as classification performed by chosen inducers capable of operating on both continuous and categorical attributes.

KW - Authorship attribution

KW - Feature

KW - Stylometry

KW - Supervised discretisation

KW - Unsupervised discretisation

UR - https://www.scopus.com/pages/publications/85075881166

U2 - 10.1007/978-3-030-31964-9_15

DO - 10.1007/978-3-030-31964-9_15

M3 - Conference contribution

AN - SCOPUS:85075881166

SN - 9783030319632

T3 - Advances in Intelligent Systems and Computing

SP - 156

EP - 166

BT - Man-Machine Interactions 6 - 6th International Conference on Man-Machine Interactions, ICMMI 2019

A2 - Gruca, Aleksandra

A2 - Deorowicz, Sebastian

A2 - Harezlak, Katarzyna

A2 - Piotrowska, Agnieszka

A2 - Czachórski, Tadeusz

PB - Springer

T2 - 6th International Conference on Man-Machine Interactions, ICMMI 2019

Y2 - 2 October 2019 through 3 October 2019

ER -

Stańczyk U. On Unsupervised and Supervised Discretisation in Mining Stylometric Features. W Gruca A, Deorowicz S, Harezlak K, Piotrowska A, Czachórski T, redaktorzy, Man-Machine Interactions 6 - 6th International Conference on Man-Machine Interactions, ICMMI 2019. Springer. 2020. str. 156-166. (Advances in Intelligent Systems and Computing). doi: 10.1007/978-3-030-31964-9_15

On Unsupervised and Supervised Discretisation in Mining Stylometric Features

Abstrakt

Seria publikacji

Konferencja

Obszary tematyczne ASJC Scopus

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