Disentangling the Thoughts: Latest News in Computational Argumentation
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Résumé
In this talk, I will present a bunch of papers on argument mining (co-)authored by the UKP Lab in Darmstadt. The papers have appeared in NAACL, TACL and related venues in 2018. In the first part, I will talk about large-scale argument search, classification and reasoning. In the second part, the focus will be on mitigating high annotation costs for argument annotation. Specifically, we tackle small-data scenarios for novel argument tasks, less-resourced languages or web-scale argument analysis tasks such as detecting fallacies. The talk presents the results of ongoing projects in Computational Argumentation at the Technische Universität Darmstadt [1]: Argumentation Analysis for the Web (ArguAna) [2], Decision Support by Means of Automatically Extracting Natural Language Arguments from Big Data (ArgumenText) [3].
[1] https://www.ukp.tu-darmstadt.de/research/research-areas/argumentation-mining/
[2] https://www.informatik.tu-darmstadt.de/ukp/research_6/current_projects/arguana/index.en.jsp
[3] https://www.argumentext.de/
Texte intégral
Short Bio
1Iryna Gurevych is professor of computer science at TU Darmstadt, where she leads the UKP Lab and the DFG-funded Research Training Group “Adaptive Preparation of Information from Heterogeneous Sources” (AIPHES). She has a broad range of research interests in natural language processing, with a focus on computational argumentation, computational lexical semantics, semantic information management, and discourse and dialogue processing. She has co-founded and co-organized the workshop series “Collaboratively Constructed Semantic Resources and their Applications to NLP”, “Argument Mining” and several research events on innovative applications of NLP to education, social sciences and humanities. More information can be found: https://www.ukp.tu-darmstadt.de/ .
Auteur
Technische Universität Darmstadt, Germany – gurevych[at]ukp.informatik.tu-darmstadt.de
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