CFP last date
20 December 2024
Call for Paper
January Edition
IJCA solicits high quality original research papers for the upcoming January edition of the journal. The last date of research paper submission is 20 December 2024

Submit your paper
Know more
The week's pick
Responsive image
Improved Shuffled Frog Leaping Algorithm with Self-Adaptive Shuffling for Fuzzy Logic PD+G Controller Optimization in Robotic Manipulators

Duc Hoang Nguyen
Random Articles
Reseach Article

Plagiarism Detection System

by Ashish Jain, Anmol Kumar Pandey, Aniket Saini
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 185 - Number 5
Year of Publication: 2023
Authors: Ashish Jain, Anmol Kumar Pandey, Aniket Saini
10.5120/ijca2023922652

Ashish Jain, Anmol Kumar Pandey, Aniket Saini . Plagiarism Detection System. International Journal of Computer Applications. 185, 5 ( Apr 2023), 1-3. DOI=10.5120/ijca2023922652

@article{ 10.5120/ijca2023922652,
author = { Ashish Jain, Anmol Kumar Pandey, Aniket Saini },
title = { Plagiarism Detection System },
journal = { International Journal of Computer Applications },
issue_date = { Apr 2023 },
volume = { 185 },
number = { 5 },
month = { Apr },
year = { 2023 },
issn = { 0975-8887 },
pages = { 1-3 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume185/number5/32698-2023922652/ },
doi = { 10.5120/ijca2023922652 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:25:19.091932+05:30
%A Ashish Jain
%A Anmol Kumar Pandey
%A Aniket Saini
%T Plagiarism Detection System
%J International Journal of Computer Applications
%@ 0975-8887
%V 185
%N 5
%P 1-3
%D 2023
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Plagiarism is frequently referred to as "literary theft" and "academic dishonesty" in the literature, and as it is a rising problem, it is important to be knowledgeable about the subject in order to avoid it and uphold ethical ideals. The proliferation of knowledge on the internet and in digital libraries has made plagiarism one of the most significant problems facing colleges, universities, and research sectors. Finding student-written materials or journals is incredibly simple thanks to the internet and sophisticated search engines. Plagiarism, then, is a widespread issue that affects many facets of our lives. It is crucial to note right now that identifying plagiarism is a difficult task. However, the need for technology is necessary for detecting plagiarism easily. Despite the fact that search engines like Google are available, it would be annoying to search phrases repeatedly to examine related resources on the internet. Because plagiarism may be automatically detected and highlighted, implementing a plagiarism detection system which will speed up the process of identifying plagiarism. All that is required is for the user to upload the paper to the detection system. Consequently, this document suggests that we have developed a software program for users and successfully tested it for plagiarism detection in student assignments. It is an efficient web-enabled system for detecting plagiarism.

References
  1. E. Walter, Cambridge Advanced Learner’s Dictionary with CD-ROM. Cambridge university press, 2008.
  2. “2012 report card,” Nov 2021.
  3. E. Marais, U. Minnaar, and D. Argles, “Plagiarism in e-learning systems: Identifying and solving the problem for practical assignments,” in Sixth IEEE International Conference on Advanced Learning Technologies (ICALT’06), pp. 822– 824, IEEE, 2006.
  4. Q. Li, S. Li, S. Zhang, J. Hu, and J. Hu, “A review of text corpus-based tourism big data mining,” Applied Sciences, vol. 9, no. 16, p. 3300, 2019.
  5. V. Liu and J. R. Curran, “Web text corpus for natural language processing,” in 11th Conference of the European Chapter of the Association for Computational Linguistics, pp. 233–240, 2006.
  6. Y. Kumar, D. Mahata, S. Aggarwal, A. Chugh, R. Maheshwari, and R. R. Shah, “Bhaav-a text corpus for emotion analysis from hindi stories,” arXiv preprint arXiv:1910.04073, 2019.
  7. R. R. Naik, M. B. Landge, and C. N. Mahender, “Development of marathi text corpus for plagiarism detection in the marathi language,” corpus, vol. 6, p. 340, 2011.
  8. S. P. Green, “Plagiarism, norms, and the limits of theft law: Some observations on the use of criminal sanctions in enforcing intellectual property rights,” Hastings LJ, vol. 54, p. 167, 2002.
  9. H. A. Chowdhury and D. K. Bhattacharyya, “Plagiarism: Taxonomy, tools and detection techniques,” arXiv preprint arXiv:1801.06323, 2018.
  10. A. H. Osman, N. Salim, and A. Abuobieda, “Survey of text plagiarism detection,” Computer Engineering and Applications Journal, vol. 1, no. 1, pp. 37–45, 2012.
  11. G. Navarro, “A guided tour to approximate string matching,” ACM computing surveys (CSUR), vol. 33, no. 1, pp. 31–88, 2001.
  12. S. S. Skiena, The algorithm design manual, vol. 2. Springer, 1998.
  13. S. Zhang, Y. Hu, and G. Bian, “Research on string similarity algorithm based on levenshtein distance,” in 2017 IEEE 2nd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), pp. 2247–2251, IEEE, 2017.
  14. Ding, W. and Marchionini, G. 1997 A Study on Video Browsing Strategies. Technical Report. University of Maryland at College Park. Fröhlich, B. and Plate, J. 2000. The cubic mouse: a new device for three-dimensional input.
Index Terms

Computer Science
Information Sciences

Keywords

Plagiarism Detection text-matching software machine learning

Powered by PhDFocusTM