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Professorships in the joint project "TAU4HSB"

Text Analysis and Understanding for Humanities, Social Sciences and Beyond

Bayerische Staatsregierung

As part of a cooperation between the universities of Würzburg, Bamberg, and Munich and the Hof University of Applied Sciences six professorships will be filled in 2021. Together with the existing professorships, these professorships will investigate and advance AI methods for text analysis and text comprehension. This joint project is part of the High-Tech Agenda Bavaria, in which artificial intelligence (AI) is a focal point.

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Text - in analog and digital form - is an important source of knowledge. Current methods of text analysis and text comprehension open up new approaches and possibilities in this field.

The new Professorships:

  • Computational Humanities (University of Würzburg)
  • Fundamentals of Language Processing (University of Bamberg)
  • Speech Generation and Dialog Systems (University of Bamberg)
  • Computational Social Science and Artificial Intelligence (University of Bamberg)
  • Artificial Intelligence and Computational Linguistics (University of Munich)
  • Resource-efficient Artificial Intelligence for Text Comprehension (Hof)

Concept and objective

The analysis and deeper understanding of texts takes a central role in knowledge management and knowledge generation. Corresponding systems have made enormous progress in recent years. While a few years ago mostly special approaches had to be developed for problems, there is now the possibility to use mature basic technologies in many application scenarios, e.g. through AI-based language models. At the same time, there remains room for optimization in various directions, and further breakthroughs can be hoped for in the basic technologies themselves.

Natural language processing is of central importance in this context because large parts of digitally available knowledge are in the form of text. Applications of text analysis and information extraction thus play a fundamental role, whereby the object of analysis must be considered on the one hand in its local structures (e.g., named-entity recognition or coreference analysis) and on the other hand as a whole (e.g., text summarization). Application domains include humanities or social sciences, where historical texts, political speeches, or texts from social media are analyzed with respect to sentiment, authorship, network structures, etc. However, the potential applications extend far beyond these fields, for example, text and language also play a central role in technical and economic application scenarios.

In order to be able to exploit the potential of the approaches in the long term, not only the effectiveness of the methods but also their (resource) efficiency is always of decisive importance. Due to its breadth in language processing and generation (positions at the LMU and in Bamberg), the application fields addressed in depth (Computational Humanities in Würzburg and Computational Social Sciences in Bamberg) as well as the targeted consideration of resource-efficient methods (Hof), the network offers a very good basis for innovative research.

The network provides for site-related and cross-site cooperation. In Bamberg, the professorship "Fundamentals of Language Processing" (goal: text comprehension) is complemented by the professorship "Speech Generation and Dialog Systems" (goal: generating text and speech). Special application-related methods of AI are researched in cooperation with the professorship "Computational Social Science and Artificial Intelligence". The professorships of the network in Würzburg, Munich and Hof offer specific methodological competencies and interface capabilities (e.g. Munich as an interface to computational linguistics, Würzburg as an interface to digital philologies and Hof with a focus on resource-efficient AI).

The professorships of the network complement each other in their orientations and are designed to strengthen the data science node in the AI Network Bavaria. A connection is made via the research area "Image and Text Analysis" of the Center for Artificial Intelligence and Data Science at the University of Würzburg (CAIDAS). With the research area "Text Analysis and Understanding for Humanities, Social Sciences and Beyond", the language processing part of this research area will be significantly enhanced.

Contact:
Prof. Dr. Andreas Henrich
Chair of Media Informatics
An der Weberei 5, 96047 Bamberg, Germany
Phone: 0951 863 285
Email: andreas.henrich(at)uni-bamberg.de