Sebastian Arnold is a research assistant at DATEXIS at Beuth University of Applied Sciences Berlin and PhD student at Université de Fribourg. He graduated as MSc.-Inf. in computer science at Technische Universität Berlin and has worked on search intentions, entity linking, topic classification and text segmentation. He is one of the main developers of the information extraction framework TeXoo, the factual search engine GoOLAP and the interactive TASTY (Tag-as-you-type) editor. Off-the-record, he enjoys manifold activities as musician, drummer and hardware hacker. Sebastian is currently writing his thesis about neural machine reading for domain-specific text resources.
- Neural document representations for machine reading
- Local topic and named entity extraction
- Answer passage retrieval
- Deep learning / machine learning
- SECTOR-CDV contextualized document vectors
- SECTOR neural model for coherent topic segmentation and classification
- WikiSection dataset for cliniclal topics in long documents
- TeXoo Java framework for text analytics with deep learning
- TASTY interactive entity linking "Tag-as-you-type"
- GoOLAP factual search engine
- Nerdle topic-expert question answering system
- Senode interactive music sequencer
Publications (see DBLP)
- Sebastian Arnold, Betty van Aken, Paul Grundmann, Felix A. Gers and Alexander Löser. Learning Contextualized Document Representations for Healthcare Answer Retrieval. To appear in WWW2020 [preprint in preparation].
- Sebastian Arnold, Rudolf Schneider, Philippe Cudré-Mauroux, Felix A. Gers and Alexander Löser. SECTOR: A Neural Model for Coherent Topic Segmentation and Classification. Transactions of the Association for Computational Linguistics 2019 Vol. 7: 169-184. [PDF] [code] [dataset] [slides]
- Rudolf Schneider, Sebastian Arnold, Tom Oberhauser, Tobias Klatt, Thomas Steffek and Alexander Löser: Smart-MD: Neural Paragraph Retrieval of Medical Topics. World Wide Web Conference (Companion). IW3C2, 2018: 203–206 [PDF]
- Sebastian Arnold, Robert Dziuba and Alexander Löser: TASTY: Interactive Entity Linking As-You-Type. COLING (Demos) 2016: 111–115 [PDF] [demo]
- Sebastian Arnold, Felix A. Gers, Torsten Kilias and Alexander Löser: Robust Named Entity Recognition in Idiosyncratic Domains. arXiv:1608.06757 [cs.CL] 2016 [PDF] [code]
- Sebastian Arnold, Alexander Löser and Torsten Kilias: Resolving Common Analytical Tasks in Text Databases. ACM Eighteenth International Workshop On Data Warehousing and OLAP. ACM 2015: 75–84 [PDF]
- Umar Maqsud, Sebastian Arnold, Michael Hülfenhaus and Alan Akbik: Nerdle: Topic-Specific Question Answering Using Wikia Seeds. 25th International Conference on Computational Linguistics: Demos. ACM 2014: 81–85 [PDF] [demo]
- Sebastian Arnold, Damian Burke, Tobias Dörsch, Bernd Löber and Andreas Lommatzsch: News Visualization based on Semantic Knowledge. International Semantic Web Conference (Posters & Demos) 2014: 5–8 [PDF]
- Alexander Löser, Sebastian Arnold and Tillmann Fiehn: The GoOLAP Fact Retrieval Framework. Lecture Notes in Business Information Processing Vol 96, Business Intelligence. Springer Berlin Heidelberg, 2012: 84–97 [PDF] [demo]
E-Mail: sarnold (at) beuth-hochschule.de