Study on Extrinsic Text Plagiarism Detection Techniques and Tools

Vani, K.; Gupta, Deepa

doi:10.25103/jestr.095.02

Cited by 20 publications

(17 citation statements)

References 8 publications

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“…Urkund was the best tool at catching similarity in copy & paste texts. The success of some of the tools tested in catching similarity in copy & paste texts has also been validated by other studies such as Turnitin (Bull et al, 2001;Kakkonen & Mozgovoy, 2010;Maurer et al, 2006;Vani & Gupta, 2016) and Docol©c (Maurer et al, 2006).…”

Section: Disguising Technique-based Coveragementioning

confidence: 70%

Testing of support tools for plagiarism detection

Foltýnek

Dlabolová

Anohina-Naumeca

et al. 2020

Int J Educ Technol High Educ

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There is a general belief that software must be able to easily do things that humans find difficult. Since finding sources for plagiarism in a text is not an easy task, there is a widespread expectation that it must be simple for software to determine if a text is plagiarized or not. Software cannot determine plagiarism, but it can work as a support tool for identifying some text similarity that may constitute plagiarism. But how well do the various systems work? This paper reports on a collaborative test of 15 web-based text-matching systems that can be used when plagiarism is suspected. It was conducted by researchers from seven countries using test material in eight different languages, evaluating the effectiveness of the systems on single-source and multi-source documents. A usability examination was also performed. The sobering results show that although some systems can indeed help identify some plagiarized content, they clearly do not find all plagiarism and at times also identify nonplagiarized material as problematic.

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Section: Disguising Technique-based Coveragementioning

confidence: 70%

Testing of support tools for plagiarism detection

Foltýnek

Dlabolová

Anohina-Naumeca

et al. 2020

Int J Educ Technol High Educ

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“…These concepts are intertwined with rookie relations. This database is used in computational linguistics and natural language processing [14]. Where the relationship between keywords in WordNet is synonymy.…”

Section: The Bitap Algorithmmentioning

confidence: 99%

“…Many tricks and techniques are taken and developed by some people to deceive in order to practice plagiarism without being detected. Therefore, in this research, a highly efficient method was compared to the previous methods which will be discussed in this research [2]. Define scientific plagiarism as stealing ideas or writings of others and self-sufficiency without mentioning the scientific sources in the research.…”

Section: Introductionmentioning

confidence: 99%

Designing Method and Algorithm of Semantic Comparison for Detecting Similarities in the Case of Fuzzy Information using Software Engineering and Medical Ontologies*

Ahmed¹,

Adel²,

Nasser³

2019

IJCA

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In this article we will discuss the work of a semantic comparison method, through which the detection of plagiarism is revealed in the fuzzy information, which we have designed an algorithm with a semantic dimension to detect plagiarism in the fuzzy information and detect impersonations such as changing the structure of speech or replacing words with synonyms and limiting technical spelling errors such as not completely writing the end of the word or unofficial and unknown abbreviations, and analyze shows the degree of similarity of the original text, and analyzes the overall evaluation of the degree of similarity of texts from the apparent structures of the text. Experiments have shown that the proposed method with a semantic dimension in the case of fuzzy information is better than sherlock method in terms of file size criterion of 6% if using word synonyms in the file and 1% in case of rewriting the file. As for the standard time taken to examine the files through the acceleration calculation, it is noted that the proposed method for the semantic dimension in the case of fuzzy information is faster in performance than the Sherlock method in the case of the use of synonyms 1.02 times and in the case of rewriting words with a value of 1.01 times in the case of file size 382 words. The results of the experiments show that the average execution time of the proposed algorithm, for finding plagiarism, is less by 3.47% compared with the Sherlock algorithm in the case of the use of synonyms and less by 1.83% compared with the Sherlock algorithm in the case of rewriting words. The algorithm works effectively as the file size increases, the gain ratio is obtained up to 2.73% in the synonym of words and 2.69% in the case of rewriting words. From the results presented in the tables, we conclude that the average error rate of the proposed algorithm is 2% lower than the error rate sherlock algorithm. The complexity of the proposed algorithm is O(m*n).

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“…Researchers have proposed numerous approaches to improve the text similarity assessment methods, e.g., semantic and syntactic analyses to better identify paraphrases, or cross-language retrieval to better detect translations [2,10,18].…”

Section: Related Workmentioning

confidence: 99%

HyPlag

Meuschke

Stange

Schubotz

et al. 2018

The 41st International ACM SIGIR Conference on Research &Amp; Development in Information Retrieval

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Current plagiarism detection systems reliably find instances of copied and moderately altered text, but often fail to detect strong paraphrases, translations, and the reuse of non-textual content and ideas. To improve upon the detection capabilities for such concealed content reuse in academic publications, we make four contributions: i) We present the first plagiarism detection approach that combines the analysis of mathematical expressions, images, citations and text. ii) We describe the implementation of this hybrid detection approach in the research prototype HyPlag. iii) We present novel visualization and interaction concepts to aid users in reviewing content similarities identified by the hybrid detection approach. iv) We demonstrate the usefulness of the hybrid detection and result visualization approaches by using HyPlag to analyze a confirmed case of content reuse present in a retracted research publication.

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Study on Extrinsic Text Plagiarism Detection Techniques and Tools

Cited by 20 publications

References 8 publications

Testing of support tools for plagiarism detection

Testing of support tools for plagiarism detection

Designing Method and Algorithm of Semantic Comparison for Detecting Similarities in the Case of Fuzzy Information using Software Engineering and Medical Ontologies*

HyPlag

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