Deutsch Intern
    Data Science Chair

    Natural Language Processing

    Digital Humanities and the application and develoment of Natural Language Processing methods is an active research field in the Data Science Chair. In projects like LitBERT, Kallimachos or CLiGS we collaborate with literary scholars and work on literary and NLP research questions. Current research topics involve for example the detection of direct speech, the classification of text types or sentiment analysis in a literary context.

    The following staff member have open topics for practica, bachelor and master theses:

    Natural Language Processing (for Novels), Digital Humanities Albin Zehe
    knowledge graphs, unstructured knowledge representations  Janna Omeliyanenko
    NLP,  Aspect-based Sentiment Analysis, Pointer Networks Jan Pfister

    In the case of excellent performance there is also the chance to submit the thesis as an article to a computer science conference and to be co-author on a scientific publication early in your studies!

    Open Topics

    05/24/2024 | Natural Language Processing

    Klassifikation von Romanen anhand von Emotions-Zeitreihen

    Romane gehören zu den Textarten, die trotz riesiger Fortschritte in den letzten Jahren die NLP immer noch vor Herausforderungen stellen: Selbst die neuesten Modelle sind nicht in der Lage, komplette Romantexte am Stück einzulesen… more
    10/13/2023 | Natural Language Processing

    Parameter Efficient Neural Networks

    As neural networks grow larger and more complex to solve new challenging tasks, they are often no longer able to run on end-user hardware and incur significant power and storage costs. For this reason, there is a need for… more
    06/05/2023 | Natural Language Processing

    Knowledge Graph Representation

    As one of their predominant research areas, the semantic web community builds knowledge graphs, which are machine-readable graphs that contain knowledge from all over the world wide web. Recently, researchers have shown great… more