2 datasets found

W
PAN-PC-09
webis.de
3250083
Updated 2009
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Martin Potthast; Benno Stein; Andreas Eiselt (2009). PAN-PC-09 [Dataset]. http://doi.org/10.5281/zenodo.3250083
Explore at:
3250083Available download formats
Unique identifier
https://doi.org/10.5281/zenodo.3250083
Dataset updated
2009
Dataset provided by
The Web Technology & Information Systems Network
Bauhaus-Universität Weimar
Leipzig University
Authors
Martin Potthast; Benno Stein; Andreas Eiselt
License
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Description
This corpus is outdated. Please use its successor PAN-PC-11.
PAN Plagiarism Corpus 2009 (PAN-PC-09)
zenodo.org
commons.datacite.org
bin
Updated Jan 24, 2020
+ more versions
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Cite
Martin Potthast; Martin Potthast; Benno Stein; Benno Stein; Andreas Eiselt; Alberto Barrón-Cedeño; Paolo Rosso; Andreas Eiselt; Alberto Barrón-Cedeño; Paolo Rosso (2020). PAN Plagiarism Corpus 2009 (PAN-PC-09) [Dataset]. http://doi.org/10.5281/zenodo.3250083
Explore at:
binAvailable download formats
Unique identifier
https://doi.org/10.5281/zenodo.3250083
Dataset updated
Jan 24, 2020
Dataset provided by
Zenodohttp://zenodo.org/
Authors
Martin Potthast; Martin Potthast; Benno Stein; Benno Stein; Andreas Eiselt; Alberto Barrón-Cedeño; Paolo Rosso; Andreas Eiselt; Alberto Barrón-Cedeño; Paolo Rosso
License
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Description
This corpus is outdated. Please use its successor PAN-PC-11: https://doi.org/10.5281/zenodo.3250095

The PAN plagiarism corpus 2009 (PAN-PC-09) is a corpus for the evaluation of automatic plagiarism detection algorithms. For research purposes the corpus can be used free of charge.

The PAN-PC-09 contains documents in which artificial plagiarism has been inserted automatically. The plagiarism cases have been constructed using a so-called random plagiarist, a computer program which constructs plagiarism according to a number of random variables. The variables include the percentage of plagiarism in the whole corpus, the percentage of plagiarism per document, the length of a single plagiarized section, and the degree of obfuscation per plagiarized section.
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