Page 225 - Emerging Trends and Innovations in Web-Based Applications and Technologies

International Journal of Trend in Scientific Research and Development (IJTSRD)
Special Issue on Emerging Trends and Innovations in Web-Based Applications and Technologies
Available Online: www.ijtsrd.com e-ISSN: 2456 – 6470

Fostering Originality in Academia: The Impact of
Originality Guard on Plagiarism Prevention

1
Kinchit V. Kawade , Khushi P. Joshi , Smita Muley , Prof. Usha Kosarkar
2
4
3
1,2,3,4 Department of Science and Technology,
1,2,3 G H Raisoni Institute of Engineering and Technology, Nagpur, Maharashtra, India
4 G H Raisoni College of Engineering and Management, Nagpur, Maharashtra, India

ABSTRACT effectively. This paper provides an in-depth examination of
In today's digital landscape, the proliferation of information the tool's architecture, functionality, and performance.
has made academic dishonesty, particularly plagiarism, a
The main contributions of this research include:
rampant issue. This unethical practice not only undermines
1. A comprehensive review of existing plagiarism detection
the validity of scholarly work but also stifles innovation, tools
creativity, and authentic thought. To address this concern,
"Originality Guard" has been developed as a cutting-edge 2. The design and development of Originality Guard, an
plagiarism detection and reporting solution. This innovative advanced plagiarism detection tool
tool accurately identifies duplicated content, promoting
originality and integrity in academic and professional 3. An evaluation of the tool's performance, including its
pursuits. By utilizing "Originality Guard," individuals can accuracy and efficiency
ensure the authenticity of their work, while educators and 4. A discussion of the implications of Originality Guard for
institutions can maintain the highest standards of academic academia and beyond
integrity.
This research aims to contribute to the development of more

effective plagiarism detection tools, ultimately helping to
Keywords: Plagiarism detection, Academic integrity,
promote academic integrity and prevent plagiarism.
Originality promotion, Educational technology, Academic
dishonesty prevention, Content analysis II. RELATED WORK
Existing plagiarism detection tools rely heavily on string
I. INTRODUCTION matching algorithms and databases of previously published
Plagiarism poses a significant threat to the integrity of work. Tools like Turnitin and Que text use these methods to
academic and professional pursuits. The act of passing off detect plagiarism, but they have limitations. For instance,
someone else's work as one's own undermines the values of they can be evaded through clever paraphrasing or
originality, creativity, and intellectual honesty that are manipulation of text.
essential to scholarly and professional advancement. Despite
Research papers have explored various approaches to
its severe consequences, plagiarism remains a pervasive
improve plagiarism detection accuracy. For example, [1]
issue, with instances reported across various disciplines and
proposed a machine learning-based approach using stylistic
levels of education. The rise of digital technologies has
features, achieving an accuracy of 85%. Another study [2]
further exacerbated the problem, making it easier for utilized natural language processing techniques to detect
individuals to access and duplicate existing content. plagiarism, reporting a precision of 90%.
The consequences of plagiarism can be severe, ranging from
However, current approaches have weaknesses. Many rely
academic penalties and damage to one's reputation to legal
on large databases of previously published work, which may
repercussions and financial losses. Moreover, plagiarism
not be comprehensive or up-to-date. Others require
undermines the trust and credibility that are essential to
significant computational resources, making them
academic and professional communities. As such, it is
impractical for large-scale use.
imperative that effective measures are taken to prevent and
detect plagiarism. A review of relevant research papers reveals gaps in existing
research. Few studies have explored the use of deep learning
Traditional plagiarism detection tools have been employed techniques for plagiarism detection, and even fewer have
to combat this issue. However, these tools have limitations. evaluated the effectiveness of these approaches in real-world
They often rely on databases of previously published work, settings.
which may not be comprehensive or up-to-date. Moreover,
these tools can be evaded through clever paraphrasing or To address these gaps, this research proposes an advanced
manipulation of text. As a result, there is a need for more plagiarism detection tool, Originality Guard, which leverages
advanced and effective plagiarism detection tools. cutting-edge technologies, including machine learning and
natural language processing.
This research paper proposes an advanced plagiarism
detection tool, Originality Guard, designed to overcome the III. PROPOSED WORK
limitations of existing tools. Originality Guard leverages This research proposes an advanced plagiarism detection
cutting-edge technologies, including machine learning and tool, Originality Guard, designed to overcome the limitations
natural language processing, to detect plagiarism more of existing tools. Originality Guard's architecture consists of
three primary components:

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