Więcej o książce
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.
Zakup książki
Citation-based plagiarism detection, Bela Gipp
- Język
- Rok wydania
- 2014
- Oprawa
- (miękka)
Metody płatności
Nikt jeszcze nie ocenił.
- Tytuł
- Citation-based plagiarism detection
- Podtytuł
- Detecting Disguised and Cross-language Plagiarism using Citation Pattern Analysis
- Język
- angielski
- Autorzy
- Bela Gipp
- Wydawca
- Springer Vieweg
- Rok wydania
- 2014
- Oprawa
- miękka
- Liczba stron
- 376
- ISBN10
- 3658063939
- ISBN13
- 9783658063931
- Seria
- Tagi
- Opis
- 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.