Disclose models, hide the data - How to make use of confidential corpora without seeing sensitive raw data

Proceedings of the 9th International Conference on Language Resources and Evaluation, LREC 2014

Volumn , Issue , 2014, Pages 4230-4237

  Faessler, Erik ^a   Hellrich, Johannes ^a   Hahn, Udo ^a  

^a FRIEDRICH SCHILLER UNIVERSITY JENA   (Germany)

Author keywords

Confidential corpora; Language models; Re usability

Indexed keywords

SECURITY OF DATA;

CONFIDENTIAL CORPORA; GERMAN LANGUAGE; LANGUAGE MODEL; LANGUAGE RESOURCES; LANGUAGE TECHNOLOGY; POS TAGGING; TEXT ANALYTICS; TOKENIZATION;

COMPUTATIONAL LINGUISTICS;

EID: 84982983860     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (13)

1. Bird, S., Klein, E., and Loper, E. (2009). Natural Language Processing with Python: Analyzing Text with the Natural Language Toolkit. O'Reilly, Sebastopol, CA.
2. Chapman, W.W., Hillert, D., Velupillai, S., and et al. (2013). Extending the NEGEX lexicon for multiple languages. In MedInfo 2013 - 14th World Congress on Medical and Health Informatics, pages 677-681.
3. Claerhout, B. and De Moor, G.J.E. (2005). Privacy protection for clinical and genomic data: The use of privacy-enhancing techniques in medicine. Journal of Medical Informatics, 74:257-265.
4. Damschroder, L.J., and Pritts, J.L., Neblo, M.A., and et al. (2007). Patients, privacy and trust: Patients' willingness to allow researchers to access their medical records. Social Science & Medicine, 64(1):223-235.
5. Hahn, U., Buyko, E., Landefeld, R., and et al. (2008). An overview of JCORE, the JULIE Lab UIMA component repository. In Towards Enhanced Interoperability for Large HLT Systems: UIMA for NLP Workshop @ LREC'08, pages 1-7.
6. Kiss, T. and Strunk, J. (2006). Unsupervised multilingual sentence boundary detection. Computational Linguistics, 32(4):485-525.
7. Meystre, S.M., Ferrández, O., and Friedlin, F.J., and et al. (2014). Text de-identification for privacy protection: A study of its impact on clinical text information content. Journal of Biomedical Informatics.
8. Petrov, S., Das, D., and McDonald, R. (2012). A universal part-of-speech tagset. In LREC '12 - 8th International Conference on Language Resources and Evaluation, pages 2089-2096.
9. Schiller, A., Teufel, S., Stöckert, C., and Thielen, C. (1999). Guidelines für das Tagging deutscher Textcorpora mit STTS (Kleines und großes Tagset). Technical report, Inst. für masch. Sprachverarbeitung, U. Stuttgart; Seminar für Sprachwissenschaft, U. Tübingen.
10. Smallwood, R.F. (2012). Safeguarding Critical E-Documents. Implementing a Program for Securing Confidential Information Assets. John Wiley, Hoboken/NJ.
11. Tomanek, K., Wermter, J., and Hahn, U. (2007). Sentence and token splitting based on conditional random fields. In PACLING '07 - 10th Conference of the Pacific Association for Computational Linguistics, pages 49-57.
12. Vetulani, Z. (2012). Language resources in a public security application with text understanding competence. A case study: POLINT-112-SMS. In Language Resources for Public Security Applications Workshop @ LREC '12, pages 54-63.
13. Wermter, J. and Hahn, U. (2004). An annotated German-language medical text corpus as language resource. In LREC 2004 - 4th International Conference on Language Resources and Evaluation, Volume 2, pages 473-476.