Automatic Identification of Document Translations in Large Multilingual Document Collections
<|reference_start|>Automatic Identification of Document Translations in Large Multilingual Document Collections: Texts and their translations are a rich linguistic resource that can be used to train and test statistics-based Machine Translation systems and many other applications. In this paper, we present a working system that can identify translations and other very similar documents among a large number of candidates, by representing the document contents with a vector of thesaurus terms from a multilingual thesaurus, and by then measuring the semantic similarity between the vectors. Tests on different text types have shown that the system can detect translations with over 96% precision in a large search space of 820 documents or more. The system was tuned to ignore language-specific similarities and to give similar documents in a second language the same similarity score as equivalent documents in the same language. The application can also be used to detect cross-lingual document plagiarism.<|reference_end|>
@article{pouliquen2006automatic,
    title={Automatic Identification of Document Translations in Large Multilingual
  Document Collections},
    author={Bruno Pouliquen, Ralf Steinberger, Camelia Ignat},
    journal={Proceedings of the International Conference 'Recent Advances in
  Natural Language Processing' (RANLP'2003), pp. 401-408. Borovets, Bulgaria,
  10 - 12 September 2003},
    year={2006},
    archivePrefix={arXiv},
    eprint={cs/0609060},
    primaryClass={cs.CL cs.IR}
}