Beschreibung
The amount and size of structured and unstructured data sources available today are both accelerating at a fast pace. This situation offers exciting opportunities. It enables the work on research topics that used to be almost inconceivable until now and thus to explore the unexplored. Since its emergence, big data is changing the way scientists and engineers approach and disrupt a whole variety of industrial, academic and social problems. The challenges accompanying this development are at least two-fold. On the one hand, the management and processing of the big data sources itself has to be supported. On the other hand, a problem that may even be more difficult is to identify and ask innovative questions that turn big data into smart data.
The talk presents uses cases in text analytics to demonstrate how unstructured big data can be used in smart contexts. The covered topics range from writing assistance with Netspeak [netspeak.org] over applying AI search heuristics for automatic constrained paraphrasing to web query understanding.
Referent*innen
Prof. Dr. Matthias Hagen
Prof. Dr. Matthias Hagen is Juniorprofessor and head of the research group "Big Data Analytics" at Bauhaus-Universität Weimar. The group focuses on algorithm development for retrieval, mining and visualization in the context of big data.
He holds a PhD in theoretical computer science from the Friedrich-Schiller-Universität Jena and was head of the research group "Intelligent Learning" at the Bauhaus-Universität Weimar. His current research interests include information retrieval and web search, big data, web mining, crowdsourcing, paraphrasing, and simulating human behavior.