Building an Argument Search Engine for the Web

Henning Wachsmuth, Martin Potthast, Khalid Al-Khatib, Yamen Ajjour, Jana Puschmann, Jiani Qu, Jonas Dorsch, Viorel Morari, Janek Bevendorff, Benno Stein

Abstract
Computational argumentation is expected to play a critical role in the future of web search. To make this happen, many search-related questions must be revisited, such as how people query for arguments, how to mine arguments from the web, or how to rank them. In this paper, we develop an argument search framework for studying these and further questions. The framework allows for the composition of approaches to acquiring, mining, assessing, indexing, querying, retrieving, ranking, and presenting arguments while relying on standard infrastructure and interfaces. Based on the framework, we build a prototype search engine, called args, that relies on an initial, freely accessible index of nearly 300k arguments crawled from reliable web resources. The framework and the argument search engine are intended as an environment for collaborative research on computational argumentation and its practical evaluation.
Anthology ID:
W17-5106
Volume:
Proceedings of the 4th Workshop on Argument Mining
Month:
September
Year:
2017
Address:
Copenhagen, Denmark
Editors:
Ivan Habernal, Iryna Gurevych, Kevin Ashley, Claire Cardie, Nancy Green, Diane Litman, Georgios Petasis, Chris Reed, Noam Slonim, Vern Walker
Venue:
ArgMining
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
49–59
Language:
URL:
https://aclanthology.org/W17-5106
DOI:
10.18653/v1/W17-5106
Bibkey:
Cite (ACL):
Henning Wachsmuth, Martin Potthast, Khalid Al-Khatib, Yamen Ajjour, Jana Puschmann, Jiani Qu, Jonas Dorsch, Viorel Morari, Janek Bevendorff, and Benno Stein. 2017. Building an Argument Search Engine for the Web. In Proceedings of the 4th Workshop on Argument Mining, pages 49–59, Copenhagen, Denmark. Association for Computational Linguistics.
Cite (Informal):
Building an Argument Search Engine for the Web (Wachsmuth et al., ArgMining 2017)
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PDF:
https://preview.aclanthology.org/naacl24-info/W17-5106.pdf
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