ITU

Natural Language Processing

Organisational unit: Research Group

IT University of Copenhagen
Rued Langgaards Vej 7
DK-2300 Copenhagen S
Denmark

Contact information

Organisation profile

Natural Language Processing (NLP) uses machine learning and other techniques to parse, analyse, translate and understand texts in human languages such as English or Danish. The work of ITU NLP researchers include transfer learning, representation learning, analysis of clinical patient records, automatic summarization, corpora building, stance detection, fake news analysis, and much more. 

  1. Journal article
  2. Published

    Sequence labelling and sequence classification with gaze: Novel uses of eye‐tracking data for Natural Language Processing

    Barrett, M. J. & Hollenstein, N., 5 Nov 2020, In: Language and Linguistics Compass. 14, 11, p. 1-16 16 p.

    Research output: Journal Article or Conference Article in JournalJournal articleResearchpeer-review

  3. Published

    Mental health-related conversations on social media and crisis episodes: a time-series regression analysis

    Kolliakou, A., Bakolis, I., Chandran, D., Derczynski, L., Werbeloff, N., Osborn, D. PJ., Bontcheva, K. & Rob, S., Feb 2020, In: Scientific Reports. 10, 1342.

    Research output: Journal Article or Conference Article in JournalJournal articleResearchpeer-review

  4. Published

    Normalisation of imprecise temporal expressions extracted from text

    Tissot, H., Roberts, A., Derczynski, L. & Didonet Del Fabro, M., 2019, In: Knowledge and Information Systems. p. 1-34

    Research output: Journal Article or Conference Article in JournalJournal articleResearchpeer-review

  5. Published

    Directions in abusive language training data, a systematic review: Garbage in, garbage out

    Vidgen, B. & Derczynski, L., 28 Dec 2020, In: PLOS ONE. 15, 12, e0243300.

    Research output: Journal Article or Conference Article in JournalJournal articleResearchpeer-review

  6. Anthology
  7. Published

    Proceedings of the 22nd Nordic Conference on Computational Linguistics

    Hartmann, M. (ed.) & Plank, B. (ed.), 1 Jun 2019, Turku, Finland: Linköping University Electronic Press. (NEALT (Northern European Association of Language Technology) Proceedings Series; No. 42).

    Research output: Book / Anthology / Report / Ph.D. thesisAnthologyResearchpeer-review

  8. Article in proceedings
  9. Published

    Matching Theory and Data with Personal-ITY: What a Corpus of Italian YouTube Comments Reveals About Personality

    Bassignana, E., Nissim, M. & Patti, V., 2020, Proceedings of the Third Workshop on Computational Modeling of People's Opinions, Personality, and Emotion's in Social Media. Association for Computational Linguistics, p. 11-22

    Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

  10. Published

    One of these words is not like the other: a reproduction of outlier identification using non-contextual word representations

    Brink Andersen, J., Bak Bertelsen, M., Hørby Schou, M., Ciosici, M. R. & Assent, I., Nov 2020, Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing and the 10th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) . Association for Computational Linguistics, 11 p.

    Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

  11. Published

    Accelerated High-Quality Mutual-Information Based Word Clustering

    Ciosici, M. R., Assent, I. & Derczynski, L., 1 May 2020, Proceedings of The 12th Language Resources and Evaluation Conference. Marseille, France: European Language Resources Association, p. 2484-2489 6 p.

    Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

  12. Published

    Quantifying the morphosyntactic content of Brown Clusters

    Ciosici, M., Derczynski, L. & Assent, I., Jun 2019, Proceedings of the Annual Conference of the North American Chapter of the Association for Computational Linguistics. Association for Computational Linguistics, Vol. 1. p. 1541–1550 N19-1157

    Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

  13. Published

    Synthetic Data for English Lexical Normalization: How Close Can We Get to Manually Annotated Data?

    Dekker, K. & van der Goot, R., May 2020, Proceedings of the Twelfth International Conference on Language Resources and Evaluation (LREC 2020). European Language Resources Association, p. 6300-6309

    Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

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