摘要： People love to argue. In recent years, Artificial Intelligence has achieved great advances in modelling natural language argumentation. While analysing and creating arguments is a highly complex (and enjoyable!) task at which even humans are not good, let alone perfect, we describe our natural language processing (NLP) research to identify arguments, their stance and aspects, aggregate arguments into topically coherent clusters, and finally, even to generate new arguments, given their desired topic, aspect and stance. The talk will tell you the story how the ArgumenText project has been conceptualized into a set of novel NLP tasks and highlight their main research outcomes. Argument mining has a tremendous number of possible applications, of which the talk discusses a few selected ones.

简历： Iryna Gurevych (PhD 2003, U. Duisburg-Essen, Germany) is a professor of Computer Science and director of the Ubiquitous Knowledge Processing (UKP) Lab at the Technical University (TU) of Darmstadt in Germany. She joined TU Darmstadt in 2005 (tenured as full professor in 2009). Her main research interest is machine learning for large-scale language understanding, including text analysis for social sciences and humanities. She is one of the co-founders of the field of computational argumentation with many applications, such as the identification of fake news and decision-making support. Iryna’s work received numerous awards, e.g. a highly competitive Lichtenberg-Professorship Award from the Volkswagen Foundation and a DFG Emmy-Noether Young Researcher’s Excellence Career Award. Iryna was elected to be President of SIGDAT, one of the most important scientific bodies in the ACL community. She was program co-chair of ACL’s most important conference in 2018, the Annual Meeting of the Association for Computational Linguistics, and she is General Chair of *SEM 2020, the 9th Joint Conference on Lexical and Computational Semantics.