ENCOPLOT: Pairwise Sequence Matching in Linear Time Applied to Plagiarism Detection ∗

Abstract

In this paper we describe a new general plagiarism detection method, that we used in our winning entry to the 1st International Competition on Plagiarism Detection, the external plagiarism detection task, which assumes the source documents are available. In the first phase of our method, a matrix of kernel values is computed, which gives a similarity value based on n-grams between each source and each suspicious document. In the second phase, each promising pair is further investigated, in order to extract the precise positions and lengths of the subtexts that have been copied and maybe obfuscated using encoplot, a novel linear time pairwise sequence matching technique. We solved the significant computational challenges arising from having to compare millions of document pairs by using a library developed by our group mainly for use in network security tools. The performance achieved is comparing more than 49 million pairs of documents in 12 hours on a single computer. The results in the challenge were very good, we outperformed all other methods.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 123 citations exist upstream.