International Conference of the Cross-Language Evaluation Forum for European Languages

Experimental IR Meets Multilinguality, Multimodality, and Interaction pp 193-199 | Cite as

Meta Text Aligner: Text Alignment Based on Predicted Plagiarism Relation

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9283)

Abstract

Text alignment is one of the main steps of plagiarism detection in textual environments. Considering the pattern in distribution of the common semantic elements of the two given documents, different strategies may be suitable for this task. In this paper we assume that the obfuscation level, i.e the plagiarism type, is a function of the distribution of the common elements in the two documents. Based on this assumption, we propose Meta Text Aligner which predicts plagiarism relation of two given documents and employs the prediction results to select the best text alignment strategy. Thus, it will potentially perform better than the existing methods which use a same strategy for all cases. As indicated by the experiments, we have been able to classify document pairs based on plagiarism type with the precision of \(89\%\). Furthermore exploiting the predictions of the classifier for choosing the proper method or the optimal configuration for each type we have been able to improve the Plagdet score of the existing methods.

Keywords

Meta Text Aligner Plagiarism type Text alignment Plagiarism detection Patterns of distribution of common elements 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Samira Abnar
    • 1
  • Mostafa Dehghani
    • 2
  • Azadeh Shakery
    • 1
  1. 1.School of ECE, College of EngineeringUniversity of TehranTehranIran
  2. 2.Institute for Logic, Language and ComputationUniversity of AmsterdamAmsterdamThe Netherlands

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