Utilizing Text Similarity Measurement for Data Compression to Detect Plagiarism in Czech

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F15%3A86092341" target="_blank" >RIV/61989100:27240/15:86092341 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/61989100:27740/15:86092341

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-319-13572-4_13" target="_blank" >http://dx.doi.org/10.1007/978-3-319-13572-4_13</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-13572-4_13" target="_blank" >10.1007/978-3-319-13572-4_13</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Utilizing Text Similarity Measurement for Data Compression to Detect Plagiarism in Czech

Popis výsledku v původním jazyce

This paper attempts to apply data compression based simi- larity method for plagiarism detection. The method has been used earlier for plagiarism detection for Arabic and English languages. In this paper we utilize this method for Czech language text from a local multi-domain Czech corpus with 50 original documents with non-plagiarized parts, and 100 suspicious documents. The documents were generated so that every document could have from 1 to 5 paragraphs. The suspicion rate in the documents was randomly chosen from 0.2 to 0.8. The ndings of the study show that the similarity measurement based on Lempel-Ziv com- parison algorithms is ecient for the plagiarized part of the Czech text documents with a success rate of 82.60%. Future studies may enhance the eciency of the algorithms by including combined and more sophis- ticated methods.

Název v anglickém jazyce

Utilizing Text Similarity Measurement for Data Compression to Detect Plagiarism in Czech

Popis výsledku anglicky

This paper attempts to apply data compression based simi- larity method for plagiarism detection. The method has been used earlier for plagiarism detection for Arabic and English languages. In this paper we utilize this method for Czech language text from a local multi-domain Czech corpus with 50 original documents with non-plagiarized parts, and 100 suspicious documents. The documents were generated so that every document could have from 1 to 5 paragraphs. The suspicion rate in the documents was randomly chosen from 0.2 to 0.8. The ndings of the study show that the similarity measurement based on Lempel-Ziv com- parison algorithms is ecient for the plagiarized part of the Czech text documents with a success rate of 82.60%. Future studies may enhance the eciency of the algorithms by including combined and more sophis- ticated methods.

Druh

D - Stať ve sborníku

CEP obor

IN - Informatika

OECD FORD obor

—

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název statě ve sborníku

Advances in Intelligent Systems and Computing. Volume 334

ISBN

978-3-319-13571-7

ISSN

2194-5357

e-ISSN

—

Počet stran výsledku

10

Strana od-do

163-182

Název nakladatele

Springer

Místo vydání

New York

Místo konání akce

Addis Ababa

Datum konání akce

17. 11. 2014

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—