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.
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
Published 2017 in ArgMining@EMNLP
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- Publication year
2017
- Venue
ArgMining@EMNLP
- Publication date
2017-09-01
- Fields of study
Computer Science
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