@InProceedings{ferrero-EtAl:2017:BUCC,
  author    = {Ferrero, J\'{e}r\'{e}my  and  Besacier, Laurent  and  Schwab, Didier  and  Agn\`{e}s, Fr\'{e}d\'{e}ric},
  title     = {Deep Investigation of Cross-Language Plagiarism Detection Methods},
  booktitle = {Proceedings of the 10th Workshop on Building and Using Comparable Corpora},
  month     = {August},
  year      = {2017},
  address   = {Vancouver, Canada},
  publisher = {Association for Computational Linguistics},
  pages     = {6--15},
  abstract  = {This paper is a deep investigation of cross-language plagiarism detection
	methods on a new recently introduced open dataset, which contains parallel and
	com- parable collections of documents with multiple characteristics (different
	genres, languages and sizes of texts). We investigate cross-language plagiarism
	detection methods for 6 language pairs on 2 granularities of text units in
	order to draw robust conclusions on the best methods while deeply analyzing
	correlations across document styles and languages.},
  url       = {http://www.aclweb.org/anthology/W17-2502}
}