Plagiarism Detection: Methods and Techniques for Academic Integrity

Running head: PLAGIARISM DETECTION
Plagiarism Detection
Name of the Student
Name of the University
Author Note

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Table of Contents
Chapter 1: Introduction........................................................................................................2
1.1 Background:...............................................................................................................2
1.2 Rationale....................................................................................................................4
1.3 Problem Statement:....................................................................................................6
1.4 Aim, Objectives and research questions:...................................................................9
1.5 Significance of the Research:..................................................................................10
1.6 Research structure:...................................................................................................12
Bibliography:.....................................................................................................................16

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Chapter 1: Introduction
1.1 Background:
Plagiarism is becoming an important factor for the researchers due to the importance and
the fast growing rates. The primary areas covered by the researchers are the faster search tools
and the effective clustering process1. There are various tools or techniques to determine the
plagiarism in the document. The main reasons for the plagiarism is the development of internet.
The development of the World Wide Web and the digital libraries increased the rate of
plagiarism in the documents. The main concern is that some people just copy and paste their
document without informing the actual owner of the document. The main objective is to use a
fast, efficient and effective plagiarism detector which will detect the plagiarism easily in the
given document. Basically plagiarism is the act off stealing someone’s writing and uploading it
with his her name without the acknowledgement of the actual writer of the document. The
plagiarism can be of five types2: Copy and paste plagiarism, Style plagiarism, idea plagiarism,
Word Switch plagiarism and Metaphor Plagiarism.
Thaw SVD or Singular Value Decomposition is one of the major tools in the application
which is used to retrieve the information. It is considered to the most appropriate technique for
the sparse matrix. There are various theorems in the SVD like: (a) “Let A is an m n rank-r
matrix. Be σ1≥· · ·≥σr Eigen values of a matrix .Then there exist orthogonal matrices U =
(u1 , . . . , ur ) and V = (v1 , . . . , vr ), whose column vectors are orthonormal, and a diagonal
matrix Σ = diag (σ1 , . . . , σr ). The decomposition A = U ΣV T is called singular value
1Franco-Salvador, Marc, Paolo Rosso, and Manuel Montes-y-Gómez. "A systematic study of knowledge graph
analysis for cross-language plagiarism detection." Information Processing & Management 52, no. 4 (2016): 550-
570.
2Miranda-Jiménez, Sabino, and Efstathios Stamatatos. "Automatic Generation of Summary Obfuscation Corpus for
Plagiarism Detection." Acta Polytechnica Hungarica 14, no. 3 (2017).

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decomposition of matrix A and numbers σ1 , . . . , σr are singular values of the matrix A.
Columns of U (or V ) are called left (or right) singular vectors of matrix A”.
The decomposition of the matrix A is conducted. It is not necessary to mention that the
right and left singular vectors are not sparse. Here there are maximum “r” non-zero singular
elements. Where “r” is smaller of two matrix dimensions. Usually the singular values fall very
quickly and thus only “k” greatest singular numbers will be considered. The corresponding
singular vector coordinates are then considered. After that, matrix A is reduced to “k” using the
singular value decomposition.
Figure 1: K-reduced Singular Value Decomposition
(Source: )
Let 0 < k < r and the singular value decomposition of A is given by:
A = U∑VT = (UkU0) ∑k 0 VkT
0 ∑0 V0T