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...

This updated and revised paper gives an overview of my PhD research. It focuses on two newly developed approaches. Citation Proximity Analysis (CPA) allows the identification of related work by analyzing the co-occurrence of citations within documents. In contrast to co-citation analysis various factors, such as the proximity of citations to each other, are taken into account. The second approa...

The task of plagiarism detection entails two main steps, suspicious candidate retrieval and pairwise document similarity analysis also called detailed analysis. In this paper we focus on the second subtask. We will report our monolingual plagiarism detection system which is used to process the Persian plagiarism corpus for the task of pairwise document similarity. To retrieve plagiarised passag...

This paper presents a survey of computer algorithms used for the detection of student plagiarism. A summary of several algorithms is provided. Common features of the different plagiarism detection algorithms are described. Ethical and administrative issues involving detected plagiarism are discussed.

Unauthorized re-use of code by students is a widespread problem in academic institutions, and raises liability issues for industry. Manual plagiarism detection is time-consuming, and current effective plagiarism detection approaches cannot be easily scaled to very large code repositories. While there are practical text-based plagiarism detection systems capable of working with large collections...

Different similarity measures are available for comparison of textual data. These similarity measures are used for plagiarism detection. This research paper proposes a new similarity measure. Moreover, this paper proposes to consider length of content for plagiarism score determination. General Terms Data mining, plagiarism detection.

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 ...

Defeating plagiarism detection systems involves determining effective approaches for greatest impact at lowest cost with the least likelihood of detection. Relatively simple techniques have been applied elsewhere for avoiding plagiarism detection, demonstrated at the last HEA-ICS conference. In this paper, we discuss defeats for seven plagiarism detection systems, including Essayrater, Seesourc...

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...

Source code plagiarism detection is a problem that has been addressed several times before; and several tools have been developed for that purpose. In this research project we investigated a set of possible disguises that can be mechanically applied to plagiarized source code to defeat plagiarism detection tools. We propose a preprocessor to be used with existing plagiarism detection tools to "...