Using grammar-profiles to intrinsically expose plagiarism in text documents

Abstract

Intrinsic plagiarism detection deals with the task of finding plagiarized sections in text documents without using a reference corpus. This paper describes a novel approach in this field by analyzing the grammar of authors and using sliding windows to find significant differences in writing styles. To find suspicious text passages, the algorithm splits a document into single sentences, calculates syntax grammar trees and builds profiles based on frequently used grammar patterns. The text is then traversed, where each window is compared to the document profile using a distance metric. Finally, all sentences that have a significantly higher distance according to a utilized Gaussian normal distribution are marked as suspicious. A preliminary evaluation of the algorithm shows very promising results. © 2013 Springer-Verlag Berlin Heidelberg.