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International Journal of Science, Strategic Management and Technology

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Plagiarism Passed
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NLP-BASED PLAGIARISM DETECTION USING TF-IDF AND COSINE SIMILARITY SYSTEM

AUTHORS:
Aravind.L.Sino
Mentor
Dr.T.R.NISHADAYANA
Affiliation
Department of Computer Science,Vels Institute of Science,Technology And Advanced Studies (VISTAS),Pallavaram, Chennai-600117,Tamil Nadu, India.
DOI: 10.55041/ijsmt.v2i5.005
CC BY 4.0 License:
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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Abstract

: This project presents the development of a plagiarism detection system using Natural Language Processing (NLP) techniques. In the modern digital era, a vast amount of information is easily accessible through the internet, which makes copying and reusing content very common. Especially in academic environments, students and researchers may unintentionally or intentionally copy content from various sources. Detecting such plagiarism manually is a difficult, time-consuming, and error-prone process. Therefore, there is a strong need for an automated system that can efficiently identify similarities between documents and ensure originality.

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Article Information
PUBLICATION DETAILS
Review Type:
Double-Blind Peer Review
License:
CC BY-NC 4.0
Volume/Issue:
Volume 02, Issue 05
Review Rounds:
2
Article Type:
Research Article
Publication Date:
May 02 2026
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Aravind.L.Sino, (2026). NLP-Based Plagiarism Detection using Tf-IDF and Cosine Similarity System. International Journal of Science, Strategic Management and Technology, 02(05). https://doi.org/10.55041/ijsmt.v2i5.005

Aravind.L.Sino, . "NLP-Based Plagiarism Detection using Tf-IDF and Cosine Similarity System." International Journal of Science, Strategic Management and Technology, vol. 02, no. 05, 2026, pp. . doi:https://doi.org/10.55041/ijsmt.v2i5.005.

Aravind.L.Sino, . "NLP-Based Plagiarism Detection using Tf-IDF and Cosine Similarity System." International Journal of Science, Strategic Management and Technology 02, no. 05 (2026). https://doi.org/https://doi.org/10.55041/ijsmt.v2i5.005.

References
[1] G. Salton and C. Buckley, “Term-weighting approaches in automatic text retrieval,” Information Processing & Management, 1988.

[2] Manning, C. D., Raghavan, P., & Schütze, H., “Introduction to Information Retrieval,” Cambridge University Press, 2008.

[3] Bird, S., Klein, E., & Loper, E., “Natural Language Processing with Python,” O’Reilly Media, 2009.

[4] Scikit-learn Documentation, https://scikit-learn.org

[5] NLTK Documentation, https://www.nltk.org

 
Ethics and Compliance
✓ All ethical standards met
This article has undergone plagiarism screening and double-blind peer review. Editorial policies have been followed. Authors retain copyright under CC BY-NC 4.0 license. The research complies with ethical standards and institutional guidelines.
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