An Enhanced Framework for Extrinsic Plagiarism Avoidance for Research Articles. | [Technical Journal • 2018]

Author(s):

1. S. Imran: University of Engineering and Technology, Taxila, Pakistan

2. M. U. G. Khan: University of Engineering and Technology, Taxila, Pakistan

3. M. Idrees: University of Engineering and Technology, Lahore, Narowal Campus, Pakistan

4. I. Muneer: University of Engineering and Technology, Lahore, Narowal Campus, Pakistan

5. M. M. Iqbal: University of Engineering and Technology, Taxila, Pakistan

Abstract:

Various approaches have been implemented for plagiarism detection used, for author's work and academic publication. There is a purpose of creating such reliable and effective plagiarism detection with increasing amount of publications. This is a serious offense where one author presents someone else's work as his ownership. Moreover, these algorithms don't consider similar sections for efficient comparison. The proposed framework performs efficient sections wise plagiarism detection and provides suggestions for improving documents. The precision, recall and accuracy based on different n-gram features are presented showing the strictness of higher level n-gram features.

Page(s): 84-92

DOI: DOI not available

Published: Journal: Technical Journal, Volume: 23, Issue: 1, Year: 2018

Keywords:

Selfplagiarism , Plagiarism Avoidance , Plagiarism Remover , Copy Detection , Extrinsic Plagiarism , Plagiarism Detection

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