An Experiment in Plagiarism Detection in Academic Research Articles Using Attributional Techniques (original) (raw)
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Plagiarism has remained a serious setback especially in the academia. It is a major source of intellectual theft since it gives credits for scientific innovations to those who do not merit them. A number of efforts have been made by researchers to tackle plagiarism. However, one perceived research gap is the need to evolve verifiable computational techniques for detecting and quantifying the degree of plagiarism in digitized documents. This current research tackles this problem through a specialized plagiarism detection and quantification algorithm. It begins with a bipartitioned search operation known as F-Search. This is followed by a purge operation which excludes the plagiarized sections discovered during the initial pass, thus giving rise to a fresh search space. The resulting search space is passed through a more thorough search operation known as T-Search. At this stage, the algorithm deals with specific plagiarism hiding tricks termed as whitespace flooding. The final output is a statistic known as the Plagiarism Index, which is a numeric value in the range [0, 1] for estimating the degree of plagiarism. The scope of this research covers the text domain. Each experimental dataset is made up of a set of two documents designed in such a way that one is assumed as the original document, while the second as a plagiarized copy. The system is designed and implemented in MATLAB.