Plagiarism: Detection Techniques and Tools

In this paper we discuss about Plagiarism. What is Plagiarism? Their types, which citation it will be avoid, this papers main features are how to detect Plagiarism and how to prevent it and also difference between Plagiarism and Copyright infringement, Plagiarism and Ghostwriting. This article saying about effective Plagiarism detecting software's and this basis identify that how much work is real and other is fraud.

Plagiarism is of digital documents seems a serious problem in today's world. Plagiarism refers to the use of others data, language and writing without proper references of the original source. Plagiarism of other author's original work is one of the big problems in publishing, science, and education. Plagiarism can be of various types. Present systems are based on the traditional approach. For verifying plagiarism, traditional methods focus on text or data matching according to keywords but fail to find brilliant plagiarism using correct web. We have suggested new strategies for finding the plagiarism in the user data using the correct web. In paper we have proposed architecture and algorithms to good finding of carbon copy using correct search, it can improve the speed of carbon copy finding system. This is verifying the user data. After the performing of this approach, the perfection of plagiarism finding system will definitely increase.

2014

Being a growing problem, plagiarism is generally defined as literary theft and academic dishonesty in the literature, and it is really has to be prevented and stick to the ethical principles. This paper presents a survey on plagiarism detection systems. Common feature of different detection systems are described.

Ahmad Zaki Abu Bakar Roliana Ibrahim

Academic dishonesty is one of the critical measures to evaluate research papers, theses and students' assignments. Therefore, plagiarism detection is an area of concern for many researchers especially in the academic field. Other fields such as plagiarized news, magazine articles and web resources are also area of concern. In that regard, many detection techniques and tools have been developed to address the problem of plagiarism. Different types of texts require different techniques to detect plagiarism. Documents to be ...

International Journal of Computer Theory and Engineering, 2012

Being a growing problem, plagiarism is generally defined as "literary theft" and "academic dishonesty" in the literature, and it is really has to be well-informed on this topic to prevent the problem and stick to the ethical principles. This paper presents a survey on plagiarism detection systems, a summary of several plagiarism types, techniques, and algorithms is provided. Common feature of deferent detection systems are described. At the end of this paper authors propose a web enabled system to detect plagiarism in documents , code and images, also this system could be used in E-Learning, E-Journal, and E-Business.

Proceedings of International Conference on Recent Trends in Machine Learning, IoT, Smart Cities and Applications, 2020

With the explosive growth of technology and the easy availability of content on the web, it creates new challenges to discriminate against the original work from plagiarized material. Content is said to be plagiarized when it is taken from other original sources without giving its reference. To address this issue Plagiarism detection tools are required. Over the years, extensive work has been done in the development of anti-plagiarism tools. This paper presents the types of plagiarism with an aim to review Extrinsic Plagiarism detection techniques using Linguistic-based features, Syntactic-based features, and Semantic-based features. Further, an overview of some current state of art methodologies and their results has been discussed on the dataset of PAN-PC 2009, PAN-PC 2010, and PAN-PC 2011. This paper also analyzes the pros and cons of some existing systems and by comparing results it also identifies that some of the systems have less potency to detect the manual and highly shuffled complex types of plagiarism such as translation obfuscation. Keywords Plagiarism detection • Extrinsic plagiarism detection • Intrinsic plagiarism detection • PAN-PC datasets 1 Introduction World Wide Web provides access to data present in the documents, databases, and other sources of information using internet service. The availability of knowledge and information in the digital form leads to "Plagiarism" by "Plagiarist". Plagiarism

International Journal of Computer Engineering and Applications, 2021

Literature is an intellectual knowledge and new arguments are being made for the theft of that literature. New technical tools are being created for this problem. It's said that "Money can be stolen, some goods can be stolen but knowledge cannot be stolen". But by stealing the same knowledge as literature, the theft of the same literature begins with writing on paper. In recent years, many online tools have been able to identify potential plagiarism in research areas. In this paper major contents are the dimensions and techniques of plagiarism, NLP problems of plagiarism identifier, problem of sentences.

iadis.net

2014

Modern technologies enable students to interact with each other much easier than in the past. This enables students to help each other with their school assignments, which can quickly lead to plagiarism. The purpose of this diploma thesis was to create an application which simplifies detecting plagiarism. It also has some functionalities which connect to social media websites and can add valuable information in detecting plagiarism. The application is designed in such a way that user can upload student submissions and then check them for plagiarism. This application supports source code plagiarism detection. After submissions have been checked (with external provider-Moss), the user can create visualisations which are based on retrieved data. Currently two types of visualisations are implemented-Graph visualisation of plagiarism and Co-Occurrence Matrix visualisation. The user can then check each plagiate and confirm or reject it. With that he can later create a list of persons which are potential plagiators and invite them on an interview to verify the suspicion of plagiarism. This application supports multiple assignments, so that the user can track each person for plagiarism through all assignments. Connection to social media websites such as Facebook and Twitter is also implemented. With that the user can retrieve information whether two persons are friends on those sites. Also a number of Google results including their names is provided. This leads to conclusion that different functionalities enable the user to get better overview of student work. With discovering plagiates the user can then determine why plagiarism has occurred in the first place and it can help him prevent this from happening in future courses.

Business Ethics and Leadership

This article compares plagiarism detection systems according to the list of criteria, compiled from the most challenging and important features for users in Ukrainian higher educational institutions. In addition it describes types of text-based plagiarism and provides an overview of the most common and serious forms of plagiarism around the world and in Ukraine in particular. The authors carried out a comparative analysis of three plagiarism detection systems − Turnitin, Unicheck, eTXT − and highlighted advantages and disadvantages of each one for the use in Ukraine. However, in further studies there might be a need for revising and expanding the list of criteria depending on the subject and the aim of using plagiarism checkers.