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Citation-based Plagiarism Detection Detecting Disguised and Cross-language Plagiarism using Citation Pattern Analysis /
Plagiarism is a problem with far-reaching consequences for the sciences. However, even today's best software-based systems can only reliably identify copy&paste plagiarism. Disguised plagiarism forms, including paraphrased text, cross-language plagiarism, as well as structural and idea plag...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Autor Corporativo: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
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Wiesbaden :
Springer Fachmedien Wiesbaden : Imprint: Springer Vieweg,
2014.
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| Edición: | 1st ed. 2014. |
| Temas: | |
| Acceso en línea: | Texto Completo |
MARC
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| 100 | 1 | |a Gipp, Bela. |e author. |4 aut |4 http://id.loc.gov/vocabulary/relators/aut | |
| 245 | 1 | 0 | |a Citation-based Plagiarism Detection |h [electronic resource] : |b Detecting Disguised and Cross-language Plagiarism using Citation Pattern Analysis / |c by Bela Gipp. |
| 250 | |a 1st ed. 2014. | ||
| 264 | 1 | |a Wiesbaden : |b Springer Fachmedien Wiesbaden : |b Imprint: Springer Vieweg, |c 2014. | |
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| 520 | |a Plagiarism is a problem with far-reaching consequences for the sciences. However, even today's best software-based systems can only reliably identify copy&paste plagiarism. Disguised plagiarism forms, including paraphrased text, cross-language plagiarism, as well as structural and idea plagiarism often remain undetected. This weakness of current systems results in a large percentage of scientific plagiarism going undetected. Bela Gipp provides an overview of the state-of-the art in plagiarism detection and an analysis of why these approaches fail to detect disguised plagiarism forms. The author proposes Citation-based Plagiarism Detection to address this shortcoming. Unlike character-based approaches, this approach does not rely on text comparisons alone, but analyzes citation patterns within documents to form a language-independent "semantic fingerprint" for similarity assessment. The practicability of Citation-based Plagiarism Detection was proven by its capability to identify so-far non-machine detectable plagiarism in scientific publications. Contents Current state of plagiarism detection approaches and systems Citation-based Plagiarism Detection Target Groups Readers interested in the problem of plagiarism in the sciences Faculty and students from all disciplines, but especially computer science The Author Bela Gipp is a postdoctoral researcher at the University of California, Berkeley. | ||
| 650 | 0 | |a Artificial intelligence. | |
| 650 | 0 | |a Computer networks . | |
| 650 | 1 | 4 | |a Artificial Intelligence. |
| 650 | 2 | 4 | |a Computer Communication Networks. |
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| 776 | 0 | 8 | |i Printed edition: |z 9783658063931 |
| 776 | 0 | 8 | |i Printed edition: |z 9783658063955 |
| 856 | 4 | 0 | |u https://doi.uam.elogim.com/10.1007/978-3-658-06394-8 |z Texto Completo |
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| 950 | |a Computer Science (SpringerNature-11645) | ||
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