Plagiarism Detection over the Web: Review

Joshi, Makarand; Khanna, Kavita

doi:10.5120/11655-7163

Cited by 7 publications

(10 citation statements)

References 8 publications

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“…This method is the hybridisation of both grammatical and semantical approach which can override the drawback of semantic based method [20,21]. It is effective to detect plagiarism in clone documents as well as restructured documents.…”

Section: C) Grammar Semantics Hybrid Based Methodsmentioning

confidence: 99%

A Review on Various Plagiarism Detection Systems Based on Exterior and Interior Method

Khan¹,

Agrawal²,

Ansari³

2018

International Journal of Advanced Research in Computer and Comm

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Plagiarism is an intellectual theft. It means representation of author's output as self-contribution without mentioning reference or attribution. Plagiarism is considered as a fraudulent act which simply means forgery of someone's fresh content by not paying any tribute. It is proliferated due to increasing access to multiple resources and simply using copy paste method. With the immense growth of internet resources new technologies and original ideas or innovative thoughts are available effortlessly due to which protection over such intellectual property is challenging, but important. Therefore, in this paper we delineate about plagiarism and then classification of plagiarism. We also discuss two main approaches-Exterior and Interior methods for plagiarism detection with their characteristics methods based on their grammar styles, lexical, syntax or Stylometric features. Further, literature analysis of various algorithms is described to find out their issues and challenges improvised scope of work in future.

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Section: C) Grammar Semantics Hybrid Based Methodsmentioning

confidence: 99%

A Review on Various Plagiarism Detection Systems Based on Exterior and Interior Method

Khan¹,

Agrawal²,

Ansari³

2018

International Journal of Advanced Research in Computer and Comm

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“…If the copied parts of the program behave the same as their original counterparts, they should have the same dependencies between the input and output variables. Since these dependencies do not change even after significant disguises have been applied to the copied code † The program dependency graph (PDG)–based clone detection is more robust than structure‐based systems 10,11 . If the behavior of the copied part in a program is the same as the original, then it must have the same dependencies between the input and output variables.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Since these dependencies do not change even after significant disguises have been applied to the copied code † ¶ The program dependency graph (PDG)-based clone detection is more robust than structure-based systems. 10,11 If the behavior of the copied part in a program is the same as the original, then it must have the same dependencies between the input and output variables. However, these dependencies, as compared to structure-based approach, do not alter even after significant changes have been applied to the cloned code.…”

Section: Literature Reviewmentioning

confidence: 99%

Detection of clone scammers in Android markets using IoT‐based edge computing

Ullah

Naeem

et al. 2019

Trans Emerging Tel Tech

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Pirated application developers find an alternate way to publish pirated versions of the same Android mobile applications (apps) on different Android markets.Therefore, a centralized, automated scrutiny system among multiple app stores is inevitable to prevent publishing pirated or cloned version of these Android applications. In this paper, we proposed an Android clone detection system for Internet of things (IoT) (Droid-IoT) devices. First, the proposed system receives an original Android application package (APK) file along with possible candidate cloned APKs over the cloud network. The system uses an apkExtractor tool to extract Dalvik Executable (DEX) files for each subject program. The Jdex decompiler is used to extract Java source files from DEXs. Then, the bag-of-word model is used to extract tokenized features from source files. Further, the weighting filters are used to zoom the importance of each token. Moreover, Synthetic Minority Oversampling is applied to retrieve balanced features for better training of data. Finally, TensorFlow with Keras deep learning model is designed to predict clones in Android applications. The experimental results have shown that Droid-IoT can successfully detect cloned apps with an accuracy of up to 96%.The primary purpose of this system is to prevent the publishing of pirated apps among different app stores under different pirated names.

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“…Insufficient acknowledgment is when a flawed citation is given. Mosaic is when due to lack of knowledge; writer ignores to giving a quotation [6].…”

Section: Figure 1 Classification Of Plagiarismmentioning

confidence: 99%

“…Paraphrasing has rearranged the work of another with the same significance. The patch is cut and pastes the parts of text from many sources [6].…”

Section: Figure 1 Classification Of Plagiarismmentioning

confidence: 99%

A Novel Approach for Plagiarism Detection in English Text

Shivani¹,

Goyal²

2016

IJCA

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Digitalization provides text easily available on web interrelated to several academic areas. So it becomes a serious problem for academic enterprises or institutes. This paper presents Plagiarism detection system for the English language. Digital World provides text easily available on web interrelated to several academic areas. So it becomes a serious problem for academic enterprises or institutes. PD means to detect the text being copied from original sources through websites, books, journals, previously published papers, online search engines, etc. this paper have presented the development of a web-based PD system to discover the similarity in English written text only. This paper is going to discuss textual based PD on an exact string matching technique through the DB and the web. The proposed system has presented concerning principal behind the system. The proposed system supports three steps: first is Pre-processing where the splitting of the input string to sentences and stop words are removed. Second is the process of sentence searching through DB and the web. Once plagiarized sentence is already there in DB then sentence directly retrieved from DB with stored URL. If searching of the sentence is not found there in DB, then plagiarized sentence is searching throughout the web ("GOOGLE") starts for both semantic and syntactic by using Cosine Similarity Approach. After Web search plagiarized sentence is stored in the DB. Thirdly, similarity analysis is performed for detail description about all plagiarized sentences with the URL (source address). As a result, the proposed system displays plagiarized sentences with the original source"s URL and percentage of Plagiarism within the input string.

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Plagiarism Detection over the Web: Review

Cited by 7 publications

References 8 publications

A Review on Various Plagiarism Detection Systems Based on Exterior and Interior Method

A Review on Various Plagiarism Detection Systems Based on Exterior and Interior Method

Detection of clone scammers in Android markets using IoT‐based edge computing

A Novel Approach for Plagiarism Detection in English Text

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