In a previous paper, we showed that analyzing citation patterns in the well-known plagiarized thesis by K. T. zu Guttenberg clearly outperformed current detection methods in identifying cross-language plagiarism. However, the experiment was a proof of concept and we did not provide a prototype. This paper presents a fully functional, web-based visualization of citation patterns for this verifie...

We present an evaluation framework for plagiarism detection.1 The framework provides performance measures that address the specifics of plagiarism detection, and the PAN-PC-10 corpus, which contains 64 558 artificial and 4 000 simulated plagiarism cases, the latter generated via Amazon’s Mechanical Turk. We discuss the construction principles behind the measures and the corpus, and we compare t...

Ferret is a fast and effective tool for detecting similarities in a group of files. Applying it to the PAN’09 corpus required modifications to meet the requirements of the competition, mainly to deal with the very large number of files, the large size of some of them, and to automate some of the decisions that would normally be made by a human operator. Ferret was able to detect numerous files ...

Plagiarism is a common place in academics, especially in courses involving programming. In this paper, XPDec, an XML-based model is introduced to detect similarities among programs that arise under plagiarism. Based upon the syntax of a specific programming language, XPDec uses an XML scheme that is suitable for the detection of plagiarism. XML documents are generated from given program sources...

Detecting academic plagiarism is a pressing problem, e.g., for educational and research institutions, funding agencies, and academic publishers. Existing plagiarism detection systems reliably identify (nearly) copied text, but o‰en fail to detect disguised forms of academic plagiarism, such as paraphrases, translations, and idea plagiarism. We present Semantic Concept PaŠern Analysis an approac...

The availability and use of computers in teaching has seen an increase in the rate of plagiarism among students because of the wide availability of electronic texts online. While computer tools that have appeared in recent years are capable of detecting simple forms of plagiarism, such as copy-paste, a number of recent research studies devoted to evaluation and comparison of plagiarism detectio...

We proposed an Architectural model for detecting plagiarism in natural language text and presented the analysis of various detection processes followed for effective plagiarism detection. Other plagiarism detection mechanisms are based on parsing techniques where sentence and word chunking is performed to extract phrases which are searched on internet in comparison to that we performed sentence...

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...