Plagiarism Detection Based on Singular Value Decomposition

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F08%3A00502249" target="_blank" >RIV/49777513:23520/08:00502249 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Plagiarism Detection Based on Singular Value Decomposition

Original language description

Plagiarism is widely spread problem that is the main focus of interest these days. In this paper, we propose a new method solving associations of phrases contained in text documents. This method, called SVDPPlag, employs Singular Value Decomposition forthis purpose. Further, we discuss other approaches to plagiarism detection and compare them with our method. To examine the efficiency of plagiarism detection methods, we used an experimental corpus of 950 text documents about politics, which were created from the standard CTK corpus. The experiments indicate that our approach significantly improves the accuracy of plagiarism detection and overcomes other methods.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

JC - Computer hardware and software

OECD FORD branch

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Project

<a href="/en/project/2C06009" target="_blank" >2C06009: Complex knowledge base tools for natural language communication with the semantic web</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2008

Confidentiality

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

Article name in the collection

Advances in Natural Language Processing, Proceedings

ISBN

978-3-540-85286-5

ISSN

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e-ISSN

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Number of pages

12

Pages from-to

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Publisher name

Springer

Place of publication

Berlin

Event location

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Event date

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Type of event by nationality

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UT code for WoS article

000258935200011