Summer School "Computational Language Technologies for Medievalists" (8.-12.7.2024) Daily Schedule

Summer School “Computational Language Technologies for Medievalists”

Graz, 8-12 July 2024

Please note that the program may be under further consideration!

Objectives: The Summer School on Natural Language Processing for Medieval Texts is designed to equip students and scholars at graduate, doctoral, and postdoctoral levels with essential skills in Natural Language Processing (NLP) and its applications in medieval studies. The program offers a hands-on approach, providing practical tools and resources to enhance research in this specialized area. To foster a collaborative and enriching learning environment, the summer school will select 20+2 participants who will be divided into four groups, mixing individuals with varying levels of Python programming knowledge. This team-based approach is aimed at optimizing the learning curve by encouraging peer learning and leveraging diverse skill sets within each group, thus enhancing the overall educational experience for all participants.

Daily Schedule

  • 09:00-10:30 — Morning Session
  • 10:30-11:00 — Coffee Break
  • 11:00-12:30 — Mid-Morning Session
  • 12:30-13:30 — Lunch Break
  • 13:30-15:00 — Afternoon Session
  • 15:00-15:30 — Coffee Break
  • 15:30-17:00 — Late Afternoon Session
  • 17:00-17:30 — Coffee Break
  • 17:30-19:00 — Special Event or Keynote
  • Evening — Reception or Social Activity

Day 1: Introduction to NLP and Text Analysis

09:00-10:30 Lucija Krusic (Univ. Graz): Python programming course for novice participant (technical)

Obligatory for Novice participants

This course introduces novice participants to the fundamentals of Python programming, covering topics such as data types, control structures, functions, and basic libraries. Participants will learn to write simple Python scripts and programs, enabling them to solve NLP-related problems through hands-on projects and exercises.

10:30-11:00 Coffee Break

11:00-12:30 Klara Venglarova (Univ. Graz): Introduction to NLP Methods

Obligatory for Novice participants

What are types and tokens? What role does a lemmatizer play? How can computers recognize names in text? This introductory course on Natural Language Processing (NLP) covers fundamental concepts and includes practical exercises to deepen your understanding.

12:30-13:30 Lunch Break

13:30-13:45 Welcome

13:45-15:00 Stefanie Dipper (Ruhr-Universität Bochum): Corpus Building

This session makes introductions to corpora and annotations, including the importance of various annotation types and methodologies for enhancing linguistic research through automated tools, with a focus on enhancing the usability and accuracy of linguistic data.

15:00-15:30 Coffee Break

15:30-17:00 Tamás Kovács (Univ. Graz): Introduction into our Working Environment (Colab, Data sets)

This introductory session will familiarize participants with our primary working environment, Google Colab, including how to access and manipulate datasets within this cloud-based platform. We will explore basic features of Colab notebooks, discuss data importation techniques, and demonstrate effective ways to interact with datasets to kickstart data-driven projects.

17:00-17:30 Coffee Break

17:30 – Jean-Baptiste Camps (École Nationale des Chartes): Computational Methods and Medieval Manuscripts (Keynote)

The written culture of Antiquity and the Middle Ages has been transmitted to us mostly through handwritten documents. Contrarily to a widespread idea, a substantial part of it remains poorly known. Today, computational methods offer new windows into the cultures of the past:artificial intelligence allows to quickly transcribe and annotate vast collections of manuscripts, while quantitative analysis sheds light on the origin of the texts. In the future, methods akin to those of evolutionary biology or ecology could help understanding the macro-evolutionary processes leading to the survival or extinction of past works of literature and of wide swathes of our human cultural heritage.

Reception

Day 2: Topic Modeling

09:00-10:30 Gabriel Viehhauser (Univ. Vienna): Topic Modeling

with Martina Scholger,Teaching Assistants: Roman Bleier, Niklas Tscherne, Nicolas Renet, Florian Atzenhofer-Baumgartner

This segment of the course will delve into topic modeling, a method used to uncover hidden thematic structures in large text corpora. Participants will learn about different algorithms such as Latent Dirichlet Allocation (LDA) and Non-negative Matrix Factorization (NMF), and apply these techniques to real datasets to identify and interpret significant topics.

10:30-11:00 Coffee Break

11:00-12:30 Mid-Morning Session

12:30-13:30 Lunch Break

13:30-15:00 Hands on with prepared task

15:00-15:30 Coffee Break

15:30-17:00 Hands on with own material

17:00-17:30 Coffee Break

17:30 – Poster Session

Day 3: Named Entity Recognition

09:00-10:30 Ismail Prada (Univ. Bern): Named Entity Recognition

with Sandy Aoun and Selina Galka, Teaching Assistants: Roman Bleier, Florian Atzenhofer-Baumgartner, Niklas Tscherne, Nicolas Renet, Klara Venglarova

This session will explore Named Entity Recognition (NER), a crucial technique in natural language processing that identifies and classifies named entities in text into predefined categories such as persons, organizations, locations, and others. Participants will learn to implement and train NER models using popular libraries like spaCy and NLTK, and apply these models to extract structured information from unstructured text data.

10:30-11:00 Coffee Break

11:00-12:30 Mid-Morning Session

12:30-13:30 Lunch Break

13:30-15:00 Hands on with prepared task

15:00-15:30 Coffee Break

15:30-17:00 Hands on with own material

17:00-17:30 Coffee Break

17:30 – Poster Session

Social Dinner

Day 4: Text Reuse and Authorship Analysis

09:00-10:30 Jeroen de Gussem (Univ. Gent): Text Reuse / Stylometry

with Tamás Kovács, Teaching Assistants: Bernhard Bauer, Florian Atzenhofer-Baumgartner, Niklas Tscherne, Nicolas Renet, Klara Venglarova

This course module will cover text reuse and authorship analysis, focusing on techniques to detect instances of text borrowing and to determine authorship in various texts. Students will explore algorithms such as cosine similarity, Jaccard index, and stylometric analysis, applying these methods to literary works and academic papers to identify patterns of reuse and attribute texts to their likely authors.

10:30-11:00 Coffee Break

11:00-12:30 Mid-Morning Session

12:30-13:30 Lunch Break

13:30-15:00 Hands on with prepared task

15:00-15:30 Coffee Break

15:30-17:00 Hands on with own material

17:00-17:30 Coffee Break

17:30 – Poster Session

City Tour

Day 5: Future Directions (LLM)

09:00-10:30 Axel Pichler (Univ. Stuttgart): LLM

This concluding session will discuss the future directions of language models, particularly large language models (LLMs), emphasizing their evolving capabilities, ethical considerations, and potential impacts on various industries. Participants will explore cutting-edge developments, such as generative adversarial networks and reinforcement learning from human feedback, and discuss how these innovations could shape the next generation of AI applications.

10:30-11:00 Coffee Break

11:00-12:30 Mid-Morning Session

12:30- Lunch Break: Excursion Buschenschank: A Buschenschank is a type of seasonal wine tavern in Austria, usually run by winemakers. They are known for serving their own wine and simple, locally sourced food, often in a rustic setting.


Thanks to the support of the university network “Human Factor in the Digital Transformation” HFDT we can offer 10 selected applicants financial support for accommodation in Graz.

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