Stab, Christian ; Daxenberger, Johannes ; Stahlhut, Chris ; Miller, Tristan ; Schiller, Benjamin ; Tauchmann, Christopher ; Eger, Steffen ; Gurevych, Iryna (2018)
ArgumenText: Searching for Arguments in Heterogeneous Sources.
The 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies. New Orleans, Louisiana (01.06.2018-06.06.2018)
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (Abstract)
Argument mining is a core technology for enabling argument search in large corpora. However, most current approaches fall short when applied to heterogeneous texts. In this paper, we present an argument retrieval system capable of retrieving sentential arguments for any given controversial topic. By analyzing the highest-ranked results extracted from Web sources, we found that our system covers 89% of arguments found in expert-curated lists of arguments from an online debate portal, and also identifies additional valid arguments.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2018 |
| Autor(en): | Stab, Christian ; Daxenberger, Johannes ; Stahlhut, Chris ; Miller, Tristan ; Schiller, Benjamin ; Tauchmann, Christopher ; Eger, Steffen ; Gurevych, Iryna |
| Art des Eintrags: | Bibliographie |
| Titel: | ArgumenText: Searching for Arguments in Heterogeneous Sources |
| Sprache: | Englisch |
| Publikationsjahr: | 11 Juni 2018 |
| Buchtitel: | Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: System Demonstrations |
| Veranstaltungstitel: | The 16th Annual Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies |
| Veranstaltungsort: | New Orleans, Louisiana |
| Veranstaltungsdatum: | 01.06.2018-06.06.2018 |
| URL / URN: | http://www.aclweb.org/anthology/N18-5005 |
| Zugehörige Links: | |
| Kurzbeschreibung (Abstract): | Argument mining is a core technology for enabling argument search in large corpora. However, most current approaches fall short when applied to heterogeneous texts. In this paper, we present an argument retrieval system capable of retrieving sentential arguments for any given controversial topic. By analyzing the highest-ranked results extracted from Web sources, we found that our system covers 89% of arguments found in expert-curated lists of arguments from an online debate portal, and also identifies additional valid arguments. |
| Freie Schlagworte: | UKP_p_ArgumenText, UKP_a_ArMin, UKP_p_DKPro |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Ubiquitäre Wissensverarbeitung DFG-Graduiertenkollegs DFG-Graduiertenkollegs > Graduiertenkolleg 1994 Adaptive Informationsaufbereitung aus heterogenen Quellen DFG-Graduiertenkollegs > Graduiertenkolleg 2222 KRITIS - Kritische Infrastrukturen. Konstruktion, Funktionskrisen und Schutz in Städten |
| Hinterlegungsdatum: | 11 Jun 2018 14:04 |
| Letzte Änderung: | 24 Jan 2020 12:03 |
| PPN: | |
| Projekte: | ArgumenText |
| Sponsoren: | German Federal Ministry of Education and Research (BMBF), the promotional reference 03VP02540 (ArgumenText) |
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