Plagiarism Detection in arXiv

We describe a large-scale application of methods for finding plagiarism and self-plagiarism in research document collections. The methods are applied to a collection of 284,834 documents collected by arXiv.org over a 14 year period, covering a few different research disciplines. The methodology efficiently detects a variety of problematic author behaviors, and heuristics are developed to reduce the number of false positives. The methods are also efficient enough to implement as a real-time submission screen for a collection many times larger.

• Type: Conference
• Year: 2006
• Where: ICDM
• Authors: Daria Sorokina, Johannes Gehrke, Simeon Warner, Paul Ginsparg
• Keywords: Data Mining, ICDM 2006, Problematic Author Behaviors, Real-time Submission Screen, Research Document Collections