Citation-based Plagiarism Detection

Detecting Disguised and Cross-language Plagiarism using Citation Pattern Analysis

  • Bela Gipp

Table of contents

  1. Front Matter
    Pages I-XXVI
  2. Bela Gipp
    Pages 1-7
  3. Bela Gipp
    Pages 9-42
  4. Bela Gipp
    Pages 43-55
  5. Bela Gipp
    Pages 57-88
  6. Bela Gipp
    Pages 89-99
  7. Bela Gipp
    Pages 101-201
  8. Bela Gipp
    Pages 203-221
  9. Back Matter
    Pages 223-350

About this book

Introduction

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.

Keywords

Citation analysis Citation-based Plagiarism Detection Detection approaches Plagiarism detection Plagiarism forms

Authors and affiliations

  • Bela Gipp
    • 1
  1. 1.Department of StatisticsUC BerkeleyBerkeleyUSA

Bibliographic information

  • DOI https://doi.org/10.1007/978-3-658-06394-8
  • Copyright Information Springer Fachmedien Wiesbaden 2014
  • Publisher Name Springer Vieweg, Wiesbaden
  • eBook Packages Computer Science
  • Print ISBN 978-3-658-06393-1
  • Online ISBN 978-3-658-06394-8
  • About this book