Personal Information

Name

Iryna Gurevych, Full Professor, Dr.
Position

Director, Ubiquitous Knowledge Processing (UKP) Lab 
Primary Appointments: Dpt. of Computer Science (FB 20), Technische Universität Darmstadt (TUDA);
Secondary Appointment: Inst. of Languages and Literature Studies, Dpt. of Historical and Social Sciences, TUDA
Coordinator: Interdisciplinary Research Priority "Knowledge Discovery in the Web" (WeRC) at TUDA;

Associated with the Leibniz-Institute for Educational Research (DIPF), Frankfurt am Main

EMail 
Prof. Dr. Iryna Gurevych
Phone 
+49 (6151) 16 - 25290
Fax 
+49 (6151) 16 - 25295
Office 
S2|02 B 110 
Address

TU Darmstadt - FB 20 
Hochschulstraße 10 
64289 Darmstadt 
Germany 

 

Research Interests

Strong background in lexical-semantics, resources and algorithms, and innovative applications of language processing to social sciences and humanities, including online publishing and educational research. Iryna Gurevych is Founder and Principal Investigator in:

  • AIPHES: the DFG-funded Research Training Group “Adaptive Information Preparation from Heterogeneous Sources”, Spokesperson

  • KDSL: the Graduate School “Knowledge Discovery in Scientific Literature”, Director

  • CEDIFOR: the BMBF-funded Centre for the Digital Foundation of Research in the Humanities, Social, and Educational Sciences, Co-Director

Further Information

  • Detailed information about Iryna’s activities can be found through the respective links in the frame to the left of this text.

  • If you are a young researcher or a student in computer science or Natural Language Processing committed to cutting-edge research and team spirit, consider joining UKP.

Current Activities

2016

Co-Chair, 3rd Workshop on Argument Mining at ACL 2016 in Berlin; co-manager of the workshop's Special Track on Debating Technologies and co-chair of the workshop's Unshared Task on Argument Mining

Co-Chair, "NLP Approaches to Computational Argumentation" tutorial at ACL 2016 in Berlin

Co-Chair, "Argument Mining" course at SSA'16 in Potsdam

2015

Co-Chair, Dagstuhl Seminar “Debating Systems”, Dagstuhl, Germany

Co-Chair, GermEval Lexical Substitution Shared Task, GSCL 2015, Duisburg-Essen, Germany

Co-Organizer, 2nd Workshop on Argumentation Mining, NAACL 2015, Denver, Colorado, USA

2015 - 2016

Scientific Advisory Board Member of EACL.

Fellow at the "Forum für interdisziplinäre Forschung" (Engl.: Board for Interdisciplinary Research) of the Technische Universität Darmstadt.

Since 2012

Member and Chair (since 08.2012) of the Scientific Advisory Board (wissenschaftlicher Beirat) of the German Society for Computational Linguistics and Language Technology (Gesellschaft für Sprachtechnologie & Computerlinguistik, GSCL)

Since 2013

Founder and Chair of the Jury for the GSCL doctoral thesis award in memory of Wolfgang Hoeppner

Highlighted Past Activities

Language Resources and Evaluation Special Issue on Collaboratively Constructed Language Resources Contributed volume: The People’s Web Meets NLP: Collaboratively Constructed Language Resources Language Processing and Knowledge in the Web: Proceedings of the 25th International Conference of the German Society for Computational Linguistics (GSCL 2013) Linked Lexical Knowledge Bases

Publications

GraphDocExplore: A Framework for the Experimental Comparison of Graph-based Document Exploration Techniques

Author Tobias Falke, Iryna Gurevych
Date September 2017
Kind Inproceedings
Book titleProceedings of the 2017 Conference on Empirical Methods in Natural Language Processing (EMNLP)
Pagesto appear
LocationCopenhagen, Denmark
KeyTUD-CS-2017-0154
Research Areas AIPHES, Ubiquitous Knowledge Processing, UKP_reviewed
Abstract Graphs have long been proposed as a tool to browse and navigate in a collection of documents in order to support exploratory search. Many techniques to automatically extract different types of graphs, showing for example entities or concepts and different relationships between them, have been suggested. While experimental evidence that they are indeed helpful exists for some of them, it is largely unknown which type of graph is most helpful for a specific exploratory task. However, carrying out experimental comparisons with human subjects is challenging and time-consuming. Towards this end, we present the GraphDocExplore framework. It provides an intuitive web interface for graph-based document exploration that is optimized for experimental user studies. Through a generic graph interface, different methods to extract graphs from text can be plugged into the system. Hence, they can be compared at minimal implementation effort in an environment that ensures controlled comparisons. The system is publicly available under an open-source license.
Website https://github.com/UKPLab/emnlp2017-graphdocexplore
Full paper (pdf)
[Export this entry to BibTeX]

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