Using Structural Information and Citation Evidence to Detect Significant Plagiarism Cases in Scientific Publications

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F12%3A86084522" target="_blank" >RIV/61989100:27240/12:86084522 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1002/asi.21651" target="_blank" >http://dx.doi.org/10.1002/asi.21651</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1002/asi.21651" target="_blank" >10.1002/asi.21651</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Using Structural Information and Citation Evidence to Detect Significant Plagiarism Cases in Scientific Publications

Popis výsledku v původním jazyce

In plagiarism detection (PD) systems, two important problems should be considered: the problem of retrieving candidate documents that are globally similar to a document q under investigation, and the problem of side-by-side comparison of q and its candidates to pinpoint plagiarized fragments in detail. In this article, the authors investigate the usage of structural information of scientific publications in both problems, and the consideration of citation evidence in the second problem. Three statistical measures namely Inverse Generic Class Frequency, Spread, and Depth are introduced to assign a degree of importance (i.e., weight) to structural components in scientific articles. A term-weighting scheme is adjusted to incorporate component-weight factors, which is used to improve the retrieval of potential sources of plagiarism. A plagiarism screening process is applied based on a measure of resemblance, in which component-weight factors are exploited to ignore less or nonsignificant p

Název v anglickém jazyce

Using Structural Information and Citation Evidence to Detect Significant Plagiarism Cases in Scientific Publications

Popis výsledku anglicky

In plagiarism detection (PD) systems, two important problems should be considered: the problem of retrieving candidate documents that are globally similar to a document q under investigation, and the problem of side-by-side comparison of q and its candidates to pinpoint plagiarized fragments in detail. In this article, the authors investigate the usage of structural information of scientific publications in both problems, and the consideration of citation evidence in the second problem. Three statistical measures namely Inverse Generic Class Frequency, Spread, and Depth are introduced to assign a degree of importance (i.e., weight) to structural components in scientific articles. A term-weighting scheme is adjusted to incorporate component-weight factors, which is used to improve the retrieval of potential sources of plagiarism. A plagiarism screening process is applied based on a measure of resemblance, in which component-weight factors are exploited to ignore less or nonsignificant p

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

IN - Informatika

OECD FORD obor

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Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2012

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Journal of the American Society for Information Science and Technology

ISSN

1532-2882

e-ISSN

—

Svazek periodika

63

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

27

Strana od-do

286-312

Kód UT WoS článku

000302157900007

EID výsledku v databázi Scopus

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