This paper presents our approach to detect plagiarism in the PAN’10 competition. To accomplish this task we applied a method which aims at detecting external plagiarism cases. The method is specially designed to detect crosslanguage plagiarism and is composed by five phases: language normalization, retrieval of candidate documents, classifier training, plagiarism analysis, and post-processing. ...

Plagiarism detection is the process of locating text reuse within a suspicious document. The plagiarism detection corpora are used for evaluating plagiarism detection systems. In this paper, we present a bilingual PersianEnglish plagiarism detection corpus. We provide our corpus for the task of text alignment corpus construction in the PAN 2015 competition. Our approach is based on parallel cor...

Currently used Plagiarism Detection Systems solely rely on textbased comparisons. They only deliver satisfying results if the plagiarized text is copied literally (copy&paste), with minor alterations (e.g. shake&paste) or is machine translated. However, if the text is paraphrased or translated by a human, the currently used methods yield a very poor performance. Using the words of Weber Wulff, ...

Determining the direction of plagiarism (who plagiarized whom in a given pair of documents) is one of the most interesting problems in the field of automatic plagiarism detection. We present here an approach using an extension of the method Encoplot, which won the 1st international competition on plagiarism detection in 2009. We have tested it on a large-scale corpus of artificial plagiarism, w...

Currently there are lots of plagiarism detection approaches. But few of them implemented and adapted for Persian languages. In this paper, our work on designing and implementation of a plagiarism detection system based on preprocessing and NLP technics will be described. And the results of testing on a corpus will be presented. Keywords— External Plagiarism, Plagiarism, Copy detection, natural ...

Plagiarism in the sense of “theft of intellectual property” has been around for as long as humans have produced work of art and research. However, easy access to the Web, large databases, and telecommunication in general, has turned plagiarism into a serious problem for publishers, researchers and educational institutions. In this paper, we concentrate on textual plagiarism (as opposed to plagi...

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...

Plagiarism detection has been considered as a classification problem which can be approximated with intrinsic strategies, considering self-based information from a given document, and external strategies, considering comparison techniques between a suspicious document and different sources. In this work, both intrinsic and external approaches for plagiarism detection are presented. First, the m...

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...