ITU

Natural Language Processing

Organisational unit: Research Group

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

Contact information

Research Group Coordinator

Leon Derczynski (leod@itu.dk)

Organisation profile

ITU NLP researches in natural language processing, with extra focus on deep learning approaches, NLP for Danish, information extraction, parsing, summarization, bias reduction, fake news detection, social media processing, and low-resource languages.


Machine understanding of natural language is a major AI challenge of our time. ITU's Natural Language Processing Group adresses this challenge in all core areas of Natural Language Processing including:

• Dependency parsing. When understanding a sentence, we need to know who did what to whom – i.e., how the words relate to each other. Parsing is a process for understanding these relations. In dependency parsing, a sentence’s syntactic structure is described using the sentence’s words and a set of relations that connect the words. ITU NLP works on building parsing tools and improving parsing practices.

• Social media. Although there’s a lot of unimportant-seeming noise and chatter on social media, it’s actually very useful – not just for targeting politics and business strategy, but also for detecting virus outbreaks and earthquakes. The highly varied language on social media is difficult to process. We focus on techniques for processing this language and ways of using social media intelligence.

• Multilingual NLP. Lots of research is done on English – but there are approximately 7000 known living languages, separated over 128 language family groups. So it’s very important to get the state of the art to work in more languages than English. As well as covering many others, ITU NLP includes special focus on the Danish languages.

• Stance detection & fake news analysis. We can estimate how true or false an online claim is by measuring the reaction around it – the stance people take to it. At ITU NLP we continue work on veracity in digital media.

• Entity detection. Finding where people, organizations and places are mentioned in text is really important for many tasks – building automatic summaries, doing business intelligence, and so on. These names are called entities, which can include things like names of drugs, genes, products, and so on. Finding these names well is tough, and a theme of research at ITU NLP.

• Deep learning approaches. Language is tough to process, and so at ITU we use modern deep learning techniques to address this huge AI challenge. We’re interested in multi-task learning, transfer learning, efficient nets, and working with new and powerful toolkits, and have a selection of GPU resources for our research computing.

• Representation learning. It’s difficult to map the language of humans, with words, to the language of computers, with numbers. Finding a way of representing words using numbers can be done automatically, which is called representation learning. At ITU we’re particularly interested in learning multilingual representations, learning representations across different domains (a domain is a specific type of language, like news articles, conversation, doctor’s notes and so on), and distributional clustering.

  1. 2020
  2. PEOPLES - THIRD WORKSHOP ON COMPUTATIONAL MODELING OF PEOPLE’S OPINIONS, PERSONALITY, AND EMOTIONS IN SOCIAL MEDIA

    Malvina Nissim (Conference Chair), Viviana Patti (Conference Chair), Barbara Plank (Conference Chair)
    13 Dec 2020

    Activity: Participating in or organising an event typesOrganisation and participation in conference

  3. European Natural Language Processing Summit (EurNLP)

    Barbara Plank (Conference Chair)
    1 Jan 2020 → …

    Activity: Participating in or organising an event typesOrganisation and participation in conference

  4. North European Association for Language Technology (External organisation)

    Barbara Plank (Chairman)
    1 Jan 202031 Dec 2021

    Activity: Membership typesMembership in committee, council, board

  5. North European Association for Language Technology (External organisation)

    Leon Derczynski (Member)
    1 Jan 202031 Dec 2021

    Activity: Membership typesMembership in committee, council, board

  6. 2019
  7. Natural Language Processing:
Learning Neural Networks to Solve Language Understanding Tasks

    Barbara Plank (Speaker)
    17 Nov 2019

    Activity: Talk or presentation typesLecture and oral contribution

  8. Keynote (Transferring NLP models across languages and domains) at Deep Learning for Low-resource NLP workshop (EMNLP)

    Barbara Plank (Speaker)
    4 Nov 2019

    Activity: Talk or presentation typesLecture and oral contribution

  9. European Natural Language Processing (EurNLP) Summit

    Barbara Plank (Program co-chair), Sebastian Ruder (Program co-chair), Sebastian Riedel (Conference Chair), Fabrizio Silvestri (Conference Chair), Armand Joulin (Conference Chair)
    11 Oct 2019

    Activity: Participating in or organising an event typesOrganisation and participation in conference

  10. Opening keynote at the NLPL Deep Learning for Natural Language Processing workshop

    Barbara Plank (Speaker)
    30 Sep 2019

    Activity: Talk or presentation typesLecture and oral contribution

  11. Invited Lecturer at the first AthNLP summer school

    Barbara Plank (Speaker)
    21 Sep 2019

    Activity: Talk or presentation typesLecture and oral contribution

  12. COST Action (External organisation)

    Barbara Plank (Member)
    9 Sep 2019 → …

    Activity: Membership typesMembership in committee, council, board

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