Plagiarism has become one of the most concerned problems since there are several kinds of plagiarism that are hard to detect. Extrinsic plagiarism is now being handled well, but intrinsic plagiarism is not. Intrinsic plagiarism detection is being distracted by the mixed up structure and the using of another word which have the same meaning. Several methods have been research to handle this prob...

In recent years, there has been a concern that the Internet has been contributing to a growth in student plagiarism. This paper reports on a study aimed at investigating if there were differences between plagiarism levels in doctoral dissertations submitted by students enrolled at traditional, brick-and-mortar institutions and those by students attending online counterparts. A sample of 368 dis...

Plagiarism detection is a growing need among educational institutions and solutions for different purposes exist. An important field in this direction is detecting cases of source-code plagiarism. In this paper, we present the tool Kato for supporting the detection of this kind of plagiarism in the area of answer-set programming (ASP). Currently, the tool is implemented for DLV programs but it ...

Automatic methods of measuring similarity between program code and natural language text pairs have been used for many years to assist humans in detecting plagiarism. For example, over the past thirty years or so, a vast number of approaches have been proposed for detecting likely plagiarism between programs written by Computer Science students. However, more recently, approaches to identifying...

This paper overviews 15 plagiarism detectors that have been evaluated within the fourth international competition on plagiarism detection at PAN’12. We report on their performances for two sub-tasks of external plagiarism detection: candidate document retrieval and detailed document comparison. Furthermore, we introduce the PAN plagiarism corpus 2012, the TIRA experimentation platform, and the ...

The purpose of this study aims at helping students define plagiarism by using a discourse analysis approach within the text of a model paper for advanced students interested in writing research papers. Inexperienced researchers are often tempted to commit several types of plagiarism across disciplines in academia. These intentional and unintentional patterns of plagiarism, which have something ...

Plagiarism involves reproducing the existing information in modified format or sometimes the original document as it is. This is quiet common among students, researchers and academicians. This has made some strong influence on research community and awareness among academic peoples to prevent such a kind of malpractice. Though there exits some commercial tools to detect plagiarism, still plagia...

Detecting and combating plagiarism from Web-based sources is a concern for administrators and instructors involved in online distance education. In this paper, we quantify copy-and-paste plagiarism among adult learners in an online geography course offered through Penn State’s World Campus Geographic Information Systems (GIS) certificate program. We also evaluate the effectiveness of an “expect...

We present a hybrid plagiarism detection architecture that operates on the two principal forms of text plagiarism. For order-preserving plagiarism, such as paraphrasing and modified cut-and-paste, it contains a text alignment component that is robust against word choice and phrasing changes that do not alter the basic ordering. And for non-order based plagiarism, such as random phrase reorderin...