This tutorial can be followed individually or at some of the venues where we regularly impart it. It offers plenty of materials, including practical content and examples in the form of Jupyter notebooks that can be run in the cloud.
When given physically, we like to have an interactive session where both instructors and participants can engage in rich discussions on the topic. Some familiarity on the matter is expected but otherwise this should not prevent you from coming if you are interested in the topic.
We divide the tutorial in two main blocks: fundamentals and applications.
- Capturing meaning from text as word embeddings.
- Neural language models and contextual embeddings.
- Knowledge graph embeddings.
- Vecsigrafo – generating hybrid knowledge representations from text corpora and knowledge graphs.
- Evaluating Vecsigrafo – beyond visual inspection and intrinsic methods.
- Vecsigrafo for knowledge graph curation and interlinking.
- Applications in multi-lingual natural language processing.
- Beyond text understanding: multi-modal machine comprehension.
Proposed application domains
- Misinformation analysis
- Scientific information management
- Classic literature