Plagiarism Detection in Large Sets of Press Agency News Articles

Kienreich, Wolfgang; Sabol, Vedran; Klieber, Werner

doi:10.1109/dexa.2006.112

Cited by 10 publications

(2 citation statements)

References 7 publications

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“…The user can set or change some of the parameters that may influence the detection process such as the number of words used for detecting similarity among statements. Several other tools have been developed for plagiarism detection such as Diff [11], SCAM [12], COPS [13], KOALA [14], SSK [15], CHECK [16], MDR [17,18,19], PPChecker [20], SNITCH [21], and Ferret [15,22,23]. They use variety of document characteristics that need different plagiarism detection approaches such as fingerprinting and fuzzy information retrieval [24].…”

Section: A Plagiarism In Documentsmentioning

confidence: 99%

A Survey on Plagiarism Detection Systems

Bin-Habtoor¹,

Zaher²

2012

IJCTE

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Abstract--Being a growing problem, plagiarism is generally defined as "literary theft" and "academic dishonesty" in the literature, and it is really has to be well-informed on this topic to prevent the problem and stick to the ethical principles. This paper presents a survey on plagiarism detection systems, a summary of several plagiarism types, techniques, and algorithms is provided. Common feature of deferent detection systems are described. At the end of this paper authors propose a web enabled system to detect plagiarism in documents , code and images, also this system could be used in E-Learning, E-Journal, and E-Business.

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Section: A Plagiarism In Documentsmentioning

confidence: 99%

A Survey on Plagiarism Detection Systems

Bin-Habtoor¹,

Zaher²

2012

IJCTE

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“…Examples include essays, paper reports, and codes of some programming languages. Several prior works are thus developed for detecting textual plagiarism [4][10] and programming code plagiarism [1]. In addition, as one may notice, the structural information which is implicitly contained in programming codes is taken as additional clues for plagiarism detection in corresponding works.…”

Section: Overview Of the Plagiarism Problemmentioning

confidence: 99%

Extending Web Search for Online Plagiarism Detection

Liu

Zhang

Chen

et al. 2007

2007 IEEE International Conference on Information Reuse and Integration

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As information technologies advance, the data amount gathered on the Internet increases at an incredible rapid speed. To solve the data overloading problem, people commonly use web search engines to find what they need. However, as search engines become an efficient and effective tool, plagiarists can grab, reassemble and redistribute text contents without much difficulty. In this paper, we develop an online detection system to reduce such misapplication of search engines. Specifically, suspicious documents are extracted and verified through the collaboration of our plagiarism detection system and search engines. With a proper design, extracted text segments are given different priorities when sending them to search engines as the ascertainment of plagiarism. This greatly reduces unnecessary and repetitive works when performing plagiarism detection.

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NewsDeps: Visualizing the Origin of Information in News Articles

et al. 2021

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In scientific publications, citations allow readers to assess the authenticity of the presented information and verify it in the original context. News articles, however, do not contain citations and only rarely refer readers to further sources. Readers often cannot assess the authenticity of the presented information as its origin is unclear. We present NewsDeps, the first approach that analyzes and visualizes where information in news articles stems from. NewsDeps employs methods from natural language processing and plagiarism detection to measure article similarity. We devise a temporal-force-directed graph that places articles as nodes chronologically. The graph connects articles by edges varying in width depending on the articles' similarity. We demonstrate our approach in a case study with two real-world scenarios. We find that NewsDeps increases efficiency and transparency in news consumption by revealing which previously published articles are the primary sources of each given article.

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Plagiarism Detection in Large Sets of Press Agency News Articles

Cited by 10 publications

References 7 publications

A Survey on Plagiarism Detection Systems

A Survey on Plagiarism Detection Systems

Extending Web Search for Online Plagiarism Detection

NewsDeps: Visualizing the Origin of Information in News Articles

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