Determining Window Size from Plagiarism Corpus for Stylometric
Features

D 2015

Determining Window Size from Plagiarism Corpus for Stylometric Features

SUCHOMEL, Šimon a Michal BRANDEJS

Základní údaje

Originální název

Determining Window Size from Plagiarism Corpus for Stylometric Features

Autoři

SUCHOMEL, Šimon (203 Česká republika, domácí) a Michal BRANDEJS (203 Česká republika, garant, domácí)

Vydání

Toulouse, France, Experimental IR Meets Multilinguality, Multimodality, and Interaction, od s. 293-299, 7 s. 2015

Nakladatel

Springer International Publishing

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

10201 Computer sciences, information science, bioinformatics

Stát vydavatele

Francie

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

tištěná verze "print"

Odkazy

Springer Link

Impakt faktor

Impact factor: 0.402 v roce 2005

Kód RIV

RIV/00216224:14330/15:00084706

Organizační jednotka

Fakulta informatiky

ISBN

978-3-319-24026-8

ISSN

DOI

http://dx.doi.org/10.1007/978-3-319-24027-5_31

UT WoS

000364677800034

Klíčová slova anglicky

plagiarism; average word frequency class; stylometry; text classification; intrinsic plagiarism

Štítky

firank_B, intrinsic plagiarism, Plagiarism, plagiarism detection, stylometric features, stylometry

Příznaky

Mezinárodní význam, Recenzováno

Změněno: 16. 11. 2015 11:33, RNDr. Šimon Suchomel, Ph.D.

Anotace

V originále

The sliding window concept is a common method for computing a profile of a document with unknown structure. This paper outlines an experiment with stylometric word-based feature in order to determine an optimal size of the sliding window. It was conducted for a vocabulary richness method called ‘average word frequency class’ using the PAN 2015 source retrieval training corpus for plagiarism detection. The paper shows the pros and cons of the stop words removal for the sliding window document profiling and discusses the utilization of the selected feature for intrinsic plagiarism detection. The experiment resulted in the recommendation of setting the sliding windows to around 100 words in length for computing the text profile using the average word frequency class stylometric feature.

Návaznosti

LG13010, projekt VaV

Název: Zastoupení ČR v European Research Consortium for Informatics and Mathematics (Akronym: ERCIM-CZ)

Investor: Ministerstvo školství, mládeže a tělovýchovy ČR, Zastoupení ČR v European Research Consortium for Informatics and Mathematics

Přiložené soubory

Determining_Window_Size_from_Plagiarism_Corpus_for_Stylometric_Features.pdf

Vyhledat podobné dokumenty

Citovat

SUCHOMEL, Šimon a Michal BRANDEJS. Determining Window Size from Plagiarism Corpus for Stylometric Features. In Mothe, Josiane and Savoy, Jacques and Kamps, Jaap and Pinel-Sauvagnat, Karen and Jones, GarethJ.F. and SanJuan, Eric and Cappellato, Linda and Ferro, Nicola. Experimental IR Meets Multilinguality, Multimodality, and Interaction. Toulouse, France: Springer International Publishing, 2015, s. 293-299. ISBN 978-3-319-24026-8. Dostupné z: https://dx.doi.org/10.1007/978-3-319-24027-5_31.

@inproceedings{1317554,
   author = {Suchomel, Šimon and Brandejs, Michal},
   address = {Toulouse, France},
   booktitle = {Experimental IR Meets Multilinguality, Multimodality, and Interaction},
   doi = {http://dx.doi.org/10.1007/978-3-319-24027-5_31},
   editor = {Mothe, Josiane and Savoy, Jacques and Kamps, Jaap and Pinel-Sauvagnat, Karen and Jones, GarethJ.F. and SanJuan, Eric and Cappellato, Linda and Ferro, Nicola},
   keywords = {plagiarism; average word frequency class; stylometry; text classification; intrinsic plagiarism},
   howpublished = {tištěná verze "print"},
   language = {eng},
   location = {Toulouse, France},
   isbn = {978-3-319-24026-8},
   pages = {293-299},
   publisher = {Springer International Publishing},
   title = {Determining Window Size from Plagiarism Corpus for Stylometric Features},
   url = {http://link.springer.com/chapter/10.1007%2F978-3-319-24027-5_31},
   year = {2015}
}

TY  - JOUR
ID  - 1317554
AU  - Suchomel, Šimon - Brandejs, Michal
PY  - 2015
TI  - Determining Window Size from Plagiarism Corpus for Stylometric Features
PB  - Springer International Publishing
CY  - Toulouse, France
SN  - 9783319240268
KW  - plagiarism
KW  - average word frequency class
KW  - stylometry
KW  - text classification
KW  - intrinsic plagiarism
UR  - http://link.springer.com/chapter/10.1007%2F978-3-319-24027-5_31
L2  - http://link.springer.com/chapter/10.1007%2F978-3-319-24027-5_31
N2  - The sliding window concept is a common method for computing a profile of a document with unknown structure. This paper outlines an experiment with stylometric word-based feature in order to determine an optimal size of the sliding window. It was conducted for a vocabulary richness method called ‘average word frequency class’ using the PAN 2015 source retrieval training corpus for plagiarism detection. The paper shows the pros and cons of the stop words removal for the sliding window document profiling and discusses the utilization of the selected feature for intrinsic plagiarism detection. The experiment resulted in the recommendation of setting the sliding windows to around 100 words in length for computing the text profile using the average word frequency class stylometric feature.
ER  -

SUCHOMEL, Šimon a Michal BRANDEJS. Determining Window Size from Plagiarism Corpus for Stylometric Features. In Mothe, Josiane and Savoy, Jacques and Kamps, Jaap and Pinel-Sauvagnat, Karen and Jones, GarethJ.F. and SanJuan, Eric and Cappellato, Linda and Ferro, Nicola. \textit{Experimental IR Meets Multilinguality, Multimodality, and Interaction}. Toulouse, France: Springer International Publishing, 2015, s.~293-299. ISBN~978-3-319-24026-8. Dostupné z: https://dx.doi.org/10.1007/978-3-319-24027-5\_{}31.

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