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Citation-based Plagiarism Detection: Detecting Disguised and Cross-language
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Citation-based Plagiarism Detection: Detecting Disguised and Cross-language Plagiarism Using Citation Pattern Analysis Paperback - 2014

by Gipp, Bela

  • New
  • Paperback

Description

Vieweg + Teubner Verlag, 2014. Paperback. New. 2014 edition. 376 pages. 8.25x6.00x0.75 inches.
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Details

  • Title Citation-based Plagiarism Detection: Detecting Disguised and Cross-language Plagiarism Using Citation Pattern Analysis
  • Author Gipp, Bela
  • Binding Paperback
  • Condition New
  • Pages 350
  • Volumes 1
  • Language ENG
  • Publisher Vieweg + Teubner Verlag
  • Date 2014
  • Illustrated Yes
  • Features Illustrated
  • Bookseller's Inventory # x-3658063939
  • ISBN 9783658063931 / 3658063939
  • Weight 1.09 lbs (0.49 kg)
  • Dimensions 8.27 x 5.83 x 0.84 in (21.01 x 14.81 x 2.13 cm)
  • Themes
    • Aspects (Academic): Science/Technology Aspects
  • Dewey Decimal Code 005.7

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From the publisher

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.

From the rear cover

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.

About the author

Bela Gipp is a postdoctoral researcher at the University of California, Berkeley.