Citation-based Plagiarism Detection
Produktnummer:
18ff1b39d36eae497c9db4ef2f791bd916
| Autor: | Gipp, Bela |
|---|---|
| Themengebiete: | Citation-based Plagiarism Detection Citation analysis Detection approaches Plagiarism detection Plagiarism forms |
| Veröffentlichungsdatum: | 14.07.2014 |
| EAN: | 9783658063931 |
| Sprache: | Englisch |
| Seitenzahl: | 350 |
| Produktart: | Kartoniert / Broschiert |
| Verlag: | Springer Fachmedien Wiesbaden GmbH |
| Untertitel: | Detecting Disguised and Cross-language Plagiarism using Citation Pattern Analysis |
Produktinformationen "Citation-based Plagiarism Detection"
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.
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