Candidate Document Retrieval for Web-Scale Text Reuse Detection

  • Matthias Hagen
  • Benno Stein
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7024)

Abstract

Given a document d, the task of text reuse detection is to find those passages in d which in identical or paraphrased form also appear in other documents. To solve this problem at web-scale, keywords representing d’s topics have to be combined to web queries. The retrieved web documents can then be delivered to a text reuse detection system for an in-depth analysis. We focus on the query formulation problem as the crucial first step in the detection process and present a new query formulation strategy that achieves convincing results: compared to a maximal termset query formulation strategy [10, 14], which is the most sensible non-heuristic baseline, we save on average 70% of the queries in realistic experiments. With respect to the candidate documents’ quality, our heuristic retrieves documents that are, on average, more similar to the given document than the results of previously published query formulation strategies [4, 8].

Keywords

Similar Document Query Formulation Internal Estimation Plagiarism Detection Candidate Query 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Matthias Hagen
    • 1
  • Benno Stein
    • 1
  1. 1.Faculty of MediaBauhaus-Universität WeimarGermany

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