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Survey and Comparison between Plagiarism Detection Tools

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.
Cite This Article
  • 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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    AU  - Mahmoud Nadim Nahas
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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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Author Information
  • Faculty of Engineering, King Abdulaziz University, Jeddah, Saudi Arabia

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