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CorpusExplorer ; Eine Software zur korpuspragmatischen Analyse
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THE INFLUENCE OF LINGUISTIC STYLE: A MATCHED-GUISE EXPERIMENT ASSESSING THE EFFECTS OF SOURCE ACCENT, ARGUMENT QUALITY, AND ISSUE INVOLVEMENT ON PERSUASION
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In: Theses and Dissertations--Communication (2022)
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К ВОПРОСУ О МОДАЛЬНЫХ ПОКАЗАТЕЛЯХ ЭВИДЕНЦИАЛЬНЫХ ЗНАЧЕНИЙ В ИНГУШСКОМ ЯЗЫКЕ ... : TO THE QUESTION OF MODAL INDICATORS OF EVIDENTIAL VALUES IN THE INGUSH LANGUAGE ...
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CORPUS LINGUISTICS IN THE LANGUAGE EDUCATION ... : КОРПУСНАЯ ЛИНГВИСТИКА В ЯЗЫКОВОМ ОБРАЗОВАНИИ ...
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CorpusExplorer ... : Eine Software zur korpuspragmatischen Analyse ...
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Recent Advances in Intelligent Source Code Generation: A Survey on Natural Language Based Studies
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In: Entropy ; Volume 23 ; Issue 9 (2021)
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Особенности перевода текстов и документов официального характера ... : Translation peculiarities of official language texts and documents ...
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Шерифова, Э.М.. - : ООО "Институт развития образования и консалтинга", 2021
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Intertextuality in foreign-language academic writing in English. A mixed-methods study of university students’ writing products and processes in source-based disciplinary assignments ...
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ИНОСТРАННЫЕ ЗАИМСТВОВАНИЯ В СЛОВООБРАЗОВАТЕЛЬНОЙ СИСТЕМЕ СОВРЕМЕННОГО ФРАНЦУЗСКОГО ЯЗЫКА ... : LOANWORDS IN THE WORD FORMATION SYSTEM OF THE MODERN FRENCH LANGUAGE ...
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The use of the subtypes of lexical transformation in the translation process of Uzbek national great novel "O'tkan kunlar" ...
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The use of the subtypes of lexical transformation in the translation process of Uzbek national great novel "O'tkan kunlar" ...
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Open Legal Data: Freie juristische Daten im Rechtsstaat ...
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Open Legal Data: Freie juristische Daten im Rechtsstaat ...
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A Call for Something Better: Classrooms as Foundations of Respectful Argument for Civic Engagement
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In: Michigan Reading Journal (2021)
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Analyzing Non-Textual Content Elements to Detect Academic Plagiarism
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Abstract:
Identifying academic plagiarism is a pressing problem, among others, for research institutions, publishers, and funding organizations. Detection approaches proposed so far analyze lexical, syntactical, and semantic text similarity. These approaches find copied, moderately reworded, and literally translated text. However, reliably detecting disguised plagiarism, such as strong paraphrases, sense-for-sense translations, and the reuse of non-textual content and ideas, is an open research problem. The thesis addresses this problem by proposing plagiarism detection approaches that implement a different concept—analyzing non-textual content in academic documents, such as citations, images, and mathematical content. The thesis makes the following research contributions. It provides the most extensive literature review on plagiarism detection technology to date. The study presents the weaknesses of current detection approaches for identifying strongly disguised plagiarism. Moreover, the survey identifies a significant research gap regarding methods that analyze features other than text. Subsequently, the thesis summarizes work that initiated the research on analyzing non-textual content elements to detect academic plagiarism by studying citation patterns in academic documents. To enable plagiarism checks of figures in academic documents, the thesis introduces an image-based detection process that adapts itself to the forms of image similarity typically found in academic work. The process includes established image similarity assessments and newly proposed use-case-specific methods. To improve the identification of plagiarism in disciplines like mathematics, physics, and engineering, the thesis presents the first plagiarism detection approach that analyzes the similarity of mathematical expressions. To demonstrate the benefit of combining non-textual and text-based detection methods, the thesis describes the first plagiarism detection system that integrates the analysis of citation-based, image-based, math-based, and text-based document similarity. The system’s user interface employs visualizations that significantly reduce the effort and time users must invest in examining content similarity. To validate the effectiveness of the proposed detection approaches, the thesis presents five evaluations that use real cases of academic plagiarism and exploratory searches for unknown cases. Real plagiarism is committed by expert researchers with strong incentives to disguise their actions. Therefore, I consider the ability to identify such cases essential for assessing the benefit of any new plagiarism detection approach. The findings of these evaluations are as follows. Citation-based plagiarism detection methods considerably outperformed text-based detection methods in identifying translated, paraphrased, and idea plagiarism instances. Moreover, citation-based detection methods found nine previously undiscovered cases of academic plagiarism. The image-based plagiarism detection process proved effective for identifying frequently observed forms of image plagiarism for image types that authors typically use in academic documents. Math-based plagiarism detection methods reliably retrieved confirmed cases of academic plagiarism involving mathematical content and identified a previously undiscovered case. Math-based detection methods offered advantages for identifying plagiarism cases that text-based methods could not detect, particularly in combination with citation-based detection methods. These results show that non-textual content elements contain a high degree of semantic information, are language-independent, and largely immutable to the alterations that authors typically perform to conceal plagiarism. Analyzing non-textual content complements text-based detection approaches and increases the detection effectiveness, particularly for disguised forms of academic plagiarism. ; published
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Keyword:
Citation Analysis; Content-based Image Retrieval; Data mining; ddc:004; Digital libraries and archives; Document representation; Evaluation of retrieval results; Image search; Information extraction; Information integration; Information Visualization; Link and co-citation analysis; Math Retrieval; Mathematics retrieval; Multilingual and cross-lingual retrieval; Natural Language Processing; Near-duplicate and plagiarism detection; Open Source Software; Plagiarism Detection; Retrieval models and ranking; Surveys and overviews; User Interaction; Users and interactive retrieval; Web searching and information discovery; Web-based interaction
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URL: https://doi.org/10.5281/zenodo.4913345 http://nbn-resolving.de/urn:nbn:de:bsz:352-2-ll951b8bh8s30
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LEXICAL TRANSFORMATIONS IN THE TRANSLATION OF TONY MORRISON'S NOVEL "SONG OF SOLOMON" ; ЛЕКСИЧНІ ТРАНСФОРМАЦІЇ У ПЕРЕКЛАДІ РОМАНУ ТОНІ МОРРІСОН «ПІСНЯ СОЛОМОНА»
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In: Записки з романо-германської філології; № 1(46) (2021) ; Writings in Romance-Germanic Philology; No. 1(46) (2021) ; 2518-7627 ; 2307-4604 (2021)
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Wow! Ehi, amico. Lascia che ti spieghi. Okay? Già. The English Element in Dubbed Italian. The Case of Animated Films.
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Analysis of referring expressions in political texts translated from English to Arabic
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