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. 2019
  2. Published

    CiteTracked: A Longitudinal Dataset of Peer Reviews and Citations

    Plank, B. & van Dalen, R., 25 Jul 2019, 4th Joint Workshop on Bibliometric-enhanced Information Retrieval and Natural Language Processing for Digital Libraries (BIRNDL 2019). Chandrasekaran, M. K. & Mayr, P. (eds.). urn:nbn:de:0074-2414-3 ed. CEUR Workshop Proceedings, Vol. Vol-2414. p. 116-122 (CEUR Workshop Proceedings, Vol. 2414).

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

  3. Published

    Lexical Resources for Low-Resource PoS Tagging in Neural Times

    Plank, B. & Klerke, S., 2019, Proceedings of the 22nd Nordic Conference on Computational Linguistics (NoDaLiDa’19) . Association for Computational Linguistics, p. 25–34 (NEALT (Northern European Association of Language Technology) Proceedings Series).

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

  4. Published

    MoRTy: Unsupervised Learning of Task-specialized Word Embeddings by Autoencoding

    Rethmeier, N. & Plank, B., 2019, Proceedings of the 4th Workshop on Representation Learning for NLP (RepL4NLP-2019)): RepL4NLP-2019. Florence: Association for Computational Linguistics, p. 49-54

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

  5. Published

    Recurrent models and lower bounds for projective syntactic decoding

    Schluter, N., 2019, Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. Association for Computational Linguistics, Vol. Volume 1 (Long and Short Papers). p. 251-260 10 p.

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

  6. Published

    Beyond task success: A closer look at jointly learning to see, ask, and GuessWhat

    Shekhar, R., Venkatesh, A., Baumgärtner, T., Bruni, E., Plank, B., Raffaella Bernardi & Raquel Fernández, Jun 2019, NAACL (North American Association for Computational Linguistics). Minneapolis: Association for Computational Linguistics

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

  7. 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

  8. Published

    An In-depth Analysis of the Effect of Lexical Normalization on the Dependency Parsing of Social Media

    van der Goot, R., Oct 2019, Proceedings of the 5th Workshop on Noisy User-generated Text (W-NUT 2019). Hong Kong, China: Association for Computational Linguistics, p. 115–120 5 p.

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

  9. 2018
  10. Published

    Stance Prediction for Russian: Data and Analysis

    Lozhnikov, N., Derczynski, L. & Mazzara, M., 2018, Proceedings of 6th International Conference in Software Engineering for Defence Applications: SEDA 2018. Springer, p. 176-186 (Advances in Intelligent Systems and Computing, Vol. 925).

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

  11. Published

    IUCM at SemEval-2018 Task 11: Similar-Topic Texts as a Comprehension Knowledge Source

    Reznikova, S. & Derczynski, L., 2018, Proceedings of the 12th International Workshop on Semantic Evaluation (SemEval-2018). Association for Computational Linguistics, p. 1068-1072

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

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