Survey and Comparison between Plagiarism Detection Tools

Mahmoud Nadim Nahas

doi:doi:10.11648/j.ajdmkd.20170202.12

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Survey and Comparison between Plagiarism Detection Tools

Mahmoud Nadim Nahas

Published in American Journal of Data Mining and Knowledge Discovery (Volume 2, Issue 2)

Received: 9 January 2017 Accepted: 21 January 2017 Published: 21 February 2017

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Abstract

With the spread of using Internet in teaching and learning, and in literature reviews, plagiarism has spread widely, where researchers take readymade researches and claim them to themselves. The action of "copy and paste" has become extensive in all fields, and the scientific research domain is no less than other spheres. This has prompted many international organizations to produce detection tools to spot plagiarism in scientific articles and research reports. Many computer programs exist to identify plagiarism in scientific papers and essays in order to establish scientific honesty and to upgrade the level of university researches. Some of these programs are free, while some are commercially available. This paper presents comparison between the most famous plagiarism detection programs. The comparison helps individuals as well as organizations to select the plagiarism detection program that is most relevant for their objectives.

Published in	American Journal of Data Mining and Knowledge Discovery (Volume 2, Issue 2)
DOI	10.11648/j.ajdmkd.20170202.12
Page(s)	50-53
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2017. Published by Science Publishing Group

Keywords

Plagiarism, Research Misconduct, Research Ethics, Internet Cheating, Plagiarism Detection Programs, Plagiarism Detection Tools

References

[1]	Ali, A. M. E. T., Abdulla, H. M. D. & Snasel, V. (2011), Overview and Comparison of Plagiarism Detection Tools. In V. Snasel, J. Pokorny & K. Richta (Eds.), CEUR Workshop Proceedings (pp. 161–172), Písek, Czech Republic: VŠB-Technical University of Ostrava.
[2]	Google (2016). Retrieved from http://www.google.com.
[3]	Klug, B. (2014). Retrieved from http://www.dustball.com/cs/plagiarism.checker.
[4]	Dupli Checker (2012). Retrieved from http://www.duplichecker.com.
[5]	Plagiarisma (2015). Retrieved from http://plagiarisma.net.
[6]	Academic Plagiarism (2014). Retrieved from https://academicplagiarism.com.
[7]	Plagiarism Checker (2016). Retrieved from http://www.plagiarismchecker.com.
[8]	PlagiServe (2015). Retrieved from http://www.plagiserve.com.
[9]	EVE Plagiarism Detection System (2000). Retrieved from http://www.canexus.com/eve/index.shtml.
[10]	Plag Aware (2012). Retrieved from http://www.plagaware.com.
[11]	PlagScan (2016). Retrieved from http://www.plagscan.com.
[12]	Academic Paradigms (2016). Retrieved from http://www.checkforplagiarism.net.
[13]	Academic Plagiarism (2016). Retrieved from http://plagiarismdetection.org.
[14]	Turnitin (2015a). Retrieved from http://en.writecheck.com.
[15]	Turnitin (2015b). Retrieved from http://www.turnitin.com.
[16]	Bull, J., Collins, C., Coughlin, E. and Sharp, D. (2001). Technical Review of Plagiarism Detection Software Report, Luton, UK: University of Luton and Computer-assisted Assessment Centre.
[17]	Turnitin (2015c). Retrieved from http://www.ithenticate.com.
[18]	Top Ten Reviews (2011). Retrieved from http://plagiarism-checker-review.toptenreviews.com.

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APA Style

Mahmoud Nadim Nahas. (2017). Survey and Comparison between Plagiarism Detection Tools. American Journal of Data Mining and Knowledge Discovery, 2(2), 50-53. https://doi.org/10.11648/j.ajdmkd.20170202.12

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ACS Style

Mahmoud Nadim Nahas. Survey and Comparison between Plagiarism Detection Tools. Am. J. Data Min. Knowl. Discov. 2017, 2(2), 50-53. doi: 10.11648/j.ajdmkd.20170202.12

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AMA Style

Mahmoud Nadim Nahas. Survey and Comparison between Plagiarism Detection Tools. Am J Data Min Knowl Discov. 2017;2(2):50-53. doi: 10.11648/j.ajdmkd.20170202.12

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@article{10.11648/j.ajdmkd.20170202.12,
  author = {Mahmoud Nadim Nahas},
  title = {Survey and Comparison between Plagiarism Detection Tools},
  journal = {American Journal of Data Mining and Knowledge Discovery},
  volume = {2},
  number = {2},
  pages = {50-53},
  doi = {10.11648/j.ajdmkd.20170202.12},
  url = {https://doi.org/10.11648/j.ajdmkd.20170202.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajdmkd.20170202.12},
  abstract = {With the spread of using Internet in teaching and learning, and in literature reviews, plagiarism has spread widely, where researchers take readymade researches and claim them to themselves. The action of "copy and paste" has become extensive in all fields, and the scientific research domain is no less than other spheres. This has prompted many international organizations to produce detection tools to spot plagiarism in scientific articles and research reports. Many computer programs exist to identify plagiarism in scientific papers and essays in order to establish scientific honesty and to upgrade the level of university researches. Some of these programs are free, while some are commercially available. This paper presents comparison between the most famous plagiarism detection programs. The comparison helps individuals as well as organizations to select the plagiarism detection program that is most relevant for their objectives.},
 year = {2017}
}

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TY  - JOUR
T1  - Survey and Comparison between Plagiarism Detection Tools
AU  - Mahmoud Nadim Nahas
Y1  - 2017/02/21
PY  - 2017
N1  - https://doi.org/10.11648/j.ajdmkd.20170202.12
DO  - 10.11648/j.ajdmkd.20170202.12
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AB  - With the spread of using Internet in teaching and learning, and in literature reviews, plagiarism has spread widely, where researchers take readymade researches and claim them to themselves. The action of "copy and paste" has become extensive in all fields, and the scientific research domain is no less than other spheres. This has prompted many international organizations to produce detection tools to spot plagiarism in scientific articles and research reports. Many computer programs exist to identify plagiarism in scientific papers and essays in order to establish scientific honesty and to upgrade the level of university researches. Some of these programs are free, while some are commercially available. This paper presents comparison between the most famous plagiarism detection programs. The comparison helps individuals as well as organizations to select the plagiarism detection program that is most relevant for their objectives.
VL  - 2
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ER  -

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Author Information

Mahmoud Nadim Nahas

Faculty of Engineering, King Abdulaziz University, Jeddah, Saudi Arabia

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APA Style

Mahmoud Nadim Nahas. (2017). Survey and Comparison between Plagiarism Detection Tools. American Journal of Data Mining and Knowledge Discovery, 2(2), 50-53. https://doi.org/10.11648/j.ajdmkd.20170202.12

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ACS Style

Mahmoud Nadim Nahas. Survey and Comparison between Plagiarism Detection Tools. Am. J. Data Min. Knowl. Discov. 2017, 2(2), 50-53. doi: 10.11648/j.ajdmkd.20170202.12

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AMA Style

Mahmoud Nadim Nahas. Survey and Comparison between Plagiarism Detection Tools. Am J Data Min Knowl Discov. 2017;2(2):50-53. doi: 10.11648/j.ajdmkd.20170202.12

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@article{10.11648/j.ajdmkd.20170202.12,
  author = {Mahmoud Nadim Nahas},
  title = {Survey and Comparison between Plagiarism Detection Tools},
  journal = {American Journal of Data Mining and Knowledge Discovery},
  volume = {2},
  number = {2},
  pages = {50-53},
  doi = {10.11648/j.ajdmkd.20170202.12},
  url = {https://doi.org/10.11648/j.ajdmkd.20170202.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajdmkd.20170202.12},
  abstract = {With the spread of using Internet in teaching and learning, and in literature reviews, plagiarism has spread widely, where researchers take readymade researches and claim them to themselves. The action of "copy and paste" has become extensive in all fields, and the scientific research domain is no less than other spheres. This has prompted many international organizations to produce detection tools to spot plagiarism in scientific articles and research reports. Many computer programs exist to identify plagiarism in scientific papers and essays in order to establish scientific honesty and to upgrade the level of university researches. Some of these programs are free, while some are commercially available. This paper presents comparison between the most famous plagiarism detection programs. The comparison helps individuals as well as organizations to select the plagiarism detection program that is most relevant for their objectives.},
 year = {2017}
}

Copy | Download

TY  - JOUR
T1  - Survey and Comparison between Plagiarism Detection Tools
AU  - Mahmoud Nadim Nahas
Y1  - 2017/02/21
PY  - 2017
N1  - https://doi.org/10.11648/j.ajdmkd.20170202.12
DO  - 10.11648/j.ajdmkd.20170202.12
T2  - American Journal of Data Mining and Knowledge Discovery
JF  - American Journal of Data Mining and Knowledge Discovery
JO  - American Journal of Data Mining and Knowledge Discovery
SP  - 50
EP  - 53
PB  - Science Publishing Group
SN  - 2578-7837
UR  - https://doi.org/10.11648/j.ajdmkd.20170202.12
AB  - With the spread of using Internet in teaching and learning, and in literature reviews, plagiarism has spread widely, where researchers take readymade researches and claim them to themselves. The action of "copy and paste" has become extensive in all fields, and the scientific research domain is no less than other spheres. This has prompted many international organizations to produce detection tools to spot plagiarism in scientific articles and research reports. Many computer programs exist to identify plagiarism in scientific papers and essays in order to establish scientific honesty and to upgrade the level of university researches. Some of these programs are free, while some are commercially available. This paper presents comparison between the most famous plagiarism detection programs. The comparison helps individuals as well as organizations to select the plagiarism detection program that is most relevant for their objectives.
VL  - 2
IS  - 2
ER  -

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