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. 

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  1. 2020
  2. Published

    Biomedical Event Extraction as Sequence Labeling

    Ramponi, A., van der Goot, R., Lombardo, R. & Plank, B., Nov 2020, Conference on Empirical Methods in Natural Language Processing. Association for Computational Linguistics

    Research output: Conference Article in Proceeding or Book/Report chapter › Article in proceedings › Research › peer-review

  3. Published

    NLP North at WNUT-2020 Task 2: Pre-training versus Ensembling for Detection of Informative COVID-19 English Tweets

    Møller, A. G., van der Goot, R. & Plank, B., Nov 2020, Proceedings of the Sixth Workshop on Noisy User-generated Text (W-NUT 2020). Association for Computational Linguistics, p. 331-336

    Research output: Conference Article in Proceeding or Book/Report chapter › Article in proceedings › Research › peer-review

  4. 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 chapter › Article in proceedings › Research › peer-review

  5. Published

    Maintaining quality in FEVER annotation

    Schulte, H., Binau, J. & Derczynski, L., 9 Jul 2020, Proceedings of the Third Workshop on Fact Extraction and VERification (FEVER): Association for Computational Linguistics. Association for Computational Linguistics, p. 42-46

    Research output: Conference Article in Proceeding or Book/Report chapter › Article in proceedings › Research › peer-review

  6. 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 chapter › Article in proceedings › Research › peer-review

  7. Published

    Offensive Language and Hate Speech Detection for Danish

    Sigurbergsson, G. & Derczynski, L., 1 May 2020, Proceedings of the International Conference on Language Resources and Evaluation: LREC 2020. European Language Resources Association, p. 3498–3508

    Research output: Conference Article in Proceeding or Book/Report chapter › Article in proceedings › Research › peer-review

  8. Published

    Cross-Domain Evaluation of Edge Detection for Biomedical Event Extraction

    Ramponi, A., Plank, B. & Lombardo, R., May 2020, Proceedings of the 12th International Conference on Language Resources and Evaluation (LREC 2020). European Language Resources Association, p. 1975 1982 p.

    Research output: Conference Article in Proceeding or Book/Report chapter › Article in proceedings › Research › peer-review

  9. Published

    The Rumour Mill: Making the Spread of Misinformation Explicit and Tangible

    Inie, N., Falk Olesen, J. & Derczynski, L., Apr 2020, The ACM CHI Conference on Human Factors in Computing Systems. Association for Computing Machinery

    Research output: Conference Article in Proceeding or Book/Report chapter › Article in proceedings › Research › peer-review

  10. 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 Journal › Journal article › Research › peer-review

  11. Published

    Buhscitu at SemEvaL-2020 Task 7: Assessing Humour in Edited News Headlines using Hand-Crafted Features and Online Knowledge Bases

    Jensen, K. N., Filrup Rasmussen, N., Wang, T., Placenti, M. & Plank, B., 2020, SemEval. Association for Computational Linguistics

    Research output: Conference Article in Proceeding or Book/Report chapter › Article in proceedings › Research › peer-review

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