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Outline

Title
Abstract
Figures
Introduction
REVIEW of Related Studies
OBJECTIVES of the Study
Result Threshold
EXPERIMENTS and Discussion
Conclusion and Future Work
References

Hybrid System for Plagiarism Detection on A Scientific Paper

Profile image of Asst. Prof. Dr. Mohammed S. H. Al-TamimiAsst. Prof. Dr. Mohammed S. H. Al-Tamimi

2021

Abstract

Plagiarism Detection Systems are critical in identifying instances of plagiarism, particularly in the educational sector whenever it comes to scientific publications and papers. Plagiarism occurs when any material is copied without the author's consent or attribution. To identify such acts, thorough knowledge of plagiarism types and classes is required. It is feasible to detect several sorts of plagiarism using current tools and methodologies. With the advancement of information and communication technologies (ICT) and the availability of online scientific publications, access to these publications has grown more convenient. Additionally, with the availability of several software text editors, plagiarism detection has become a crucial concern. Numerous scholarly articles have previously examined plagiarism detection and the two most often used datasets for plagiarism detection, WordNet and the PAN Dataset. The researchers described verbatim plagiarism detection as a straightforward case of copying and pasting, and then shed light on clever plagiarism, which is more difficult to detect since it may involve original text alteration, borrowing ideas from other studies, and Other scholars have said that plagiarism can obscure the scientific content by substituting terms, deleting or introducing material, rearranging or changing the original publications. The suggested system incorporated natural language processing (NLP) and machine learning (ML) techniques, as well as an external plagiarism detection strategy based on text mining and similarity analysis. The suggested technique employs a mix of Jaccard and cosine similarity. It was examined using the PAN-PC-11 corpus. The proposed system outperforms previous systems on the PAN-PC-11, as demonstrated by the findings. Additionally, the proposed system obtains an accuracy of 0.96, a recall of 0.86, an F-measure of 0.86, and a PlagDet score of 0.86. (0.86). 0.865 and the proposed technique is substantiated by a design application that is used to detect plagiarism in scientific publications and generate nonmedication notifications. Portable Document Format (PDF) .

Figures (8)
5.Dataset Used
5.Dataset Used
As a means of increasing efficiency and performance, cosine similarity is used to calculate the number of vectot cosine angles in documents and to construct a hierarchical clustering method for them. The fowling methoc demonstrates cosine similarity in the proposed system: 9. Result Threshold
As a means of increasing efficiency and performance, cosine similarity is used to calculate the number of vectot cosine angles in documents and to construct a hierarchical clustering method for them. The fowling methoc demonstrates cosine similarity in the proposed system: 9. Result Threshold
In words, if any sentence( s) has one similarity measure, or both, exceeds the threshold of each measure is considered a plagiarized sentence. For document D. the adaptive threshold work in the following algorithm: Algorithem4. hybrid system 11.Experiments and Discussion To facilitate comprehension of the proposed system, researchers will outline its components and compare it to another system's dataset, PAN-PC-2011. The method of plagiarism between the source and suspect documents in the data set will be explained in the same step-by-step fashion as the algorithm above. an all the stages will be run on each item in each folder of the suspect folder that contains the resource folder, so the procedure of each step will be conducted in a one-to-many fashion. The implementation method is to take a document from the suspect folder and pass it on to all the source folders, and this process was used to evaluate the proposed system's algorithm's efficiency and to extract the error rate for the purpose of evaluation in order to obtain an accurate result. The best result of the two measurements used in the proposed system (cosine and Jaccard) is r. When the experiment is conducted on a data set, the hybrid system established on the Jaccard threshold (0.2) and the Cosine
In words, if any sentence( s) has one similarity measure, or both, exceeds the threshold of each measure is considered a plagiarized sentence. For document D. the adaptive threshold work in the following algorithm: Algorithem4. hybrid system 11.Experiments and Discussion To facilitate comprehension of the proposed system, researchers will outline its components and compare it to another system's dataset, PAN-PC-2011. The method of plagiarism between the source and suspect documents in the data set will be explained in the same step-by-step fashion as the algorithm above. an all the stages will be run on each item in each folder of the suspect folder that contains the resource folder, so the procedure of each step will be conducted in a one-to-many fashion. The implementation method is to take a document from the suspect folder and pass it on to all the source folders, and this process was used to evaluate the proposed system's algorithm's efficiency and to extract the error rate for the purpose of evaluation in order to obtain an accurate result. The best result of the two measurements used in the proposed system (cosine and Jaccard) is r. When the experiment is conducted on a data set, the hybrid system established on the Jaccard threshold (0.2) and the Cosine
Figure 8. Plagiarism Algorithms Comparison And the Figure 8 is Plagiarism Algorithms Comparison
Figure 8. Plagiarism Algorithms Comparison And the Figure 8 is Plagiarism Algorithms Comparison
Several PD methods and their findings have been reported in the literature in recent years. The findings of the suggested approach are compared to some of the approaches mentioned in the literature in this section. Table 3.3 compares the detection measurement in the confusion matrix obtained by the proposed method to that obtained in prior investigations. Our proposed strategy appears to be superior to others based on the stated results. Table2. Comparison with Previous Studies
Several PD methods and their findings have been reported in the literature in recent years. The findings of the suggested approach are compared to some of the approaches mentioned in the literature in this section. Table 3.3 compares the detection measurement in the confusion matrix obtained by the proposed method to that obtained in prior investigations. Our proposed strategy appears to be superior to others based on the stated results. Table2. Comparison with Previous Studies

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