Tilman Beck M.Sc.
Dept. 20: Computer Science
Ubiquitous Knowledge Processing (UKP) Lab
work +49 6151 16-57575
- Natural Language Processing (NLProc) with focus on
- argumentation mining
- unsupervised text clustering
- text summarization
- deep learning in NLProc
- Besides that I have a natural interest in
- (automatic) language learning
- ethics in NLProc
Aggregation and temporal analysis of public discourse about critical infrastructures (working title)
Given the growth of online mass communication (e.g. social media) in modern society, we can observe public discourse about the functionality of critical infrastructures.
Especially the occurrence of outages or restricted uses of those infrastructures can be observed almost in real-time in this kind of data. With the recent advancements in natural language processing through the use of deep learning techniques, we can develop models to foster the understanding of human-generated text and analyze this data on a large-scale.
The focus of my PhD project is the development and application of computational models for the detection and analysis of public discourse. First, given the vast amount of available data, I want to explore how to aggregate this information into redundant-free and meaningful summaries. Further, I am interested in analyzing the temporal evolution of public discourse on critical infrastructures.