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Content-Based Scientific Figure Plagiarism Detection Using Semantic Mapping

  • Taiseer Abdalla Elfadil EisaEmail author
  • Naomie Salim
  • Abdelzahir Abdelmaboud
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1073)

Abstract

Plagiarism is to steal others’ work using their words directly or indirectly without a credit citation. Copying others’ ideas is another type of plagiarism that may occur in many areas but the most serious one is the academic plagiarism. Academic misconduct forms high-profile plagiarism cases at universities. Therefore, technical solutions are strictly demanded for automatic idea plagiarism detection. Detection of figure plagiarism is a challenge field of research because not only the text analytics but also graphic features are analyzed. This paper investigates the issue of idea and figure plagiarism and proposes a detection method which copes with text and structure change. The procedure depends on finding similar semantic meanings between figures by applying image processing and semantic mapping techniques.

Keywords

Plagiarism detection Figure plagiarism detection Semantic meanings Scientific publications 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Taiseer Abdalla Elfadil Eisa
    • 1
    Email author
  • Naomie Salim
    • 2
  • Abdelzahir Abdelmaboud
    • 3
  1. 1.College of Science and Arts - Girls SectionKing Khalid UniversityMahayilSaudi Arabia
  2. 2.Faculty of Computer Science and Information SystemsUniversiti Teknologi MalaysiaSkudaiMalaysia
  3. 3.College of Science and Arts KingKhalid UniversityMahayilSaudi Arabia

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