Abstract
In this paper we look at the manual analysis of arguments and how this compares
to the current state of automatic argument analysis. These considerations are used to develop a new approach combining a machine learning algorithm to extract propositions from text, with a topic model to determine argument structure. The results of this method are compared to a manual analysis.
to the current state of automatic argument analysis. These considerations are used to develop a new approach combining a machine learning algorithm to extract propositions from text, with a topic model to determine argument structure. The results of this method are compared to a manual analysis.
Original language | English |
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Title of host publication | Proceedings of the First Workshop on Argumentation Mining |
Subtitle of host publication | ACL 2014 |
Publisher | Association for Computational Linguistics |
Pages | 79-87 |
Number of pages | 9 |
ISBN (Electronic) | 978-1-941643-06-8 |
Publication status | Published - 2014 |
Event | First Workshop on Argumentation Mining: 52nd Annual Meeting of the Association for Computational Linguistics - Baltimore, United States Duration: 26 Jun 2014 → … http://www.uncg.edu/cmp/ArgMining2014/ http://acl2014.org/home.htm |
Conference
Conference | First Workshop on Argumentation Mining |
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Country/Territory | United States |
City | Baltimore |
Period | 26/06/14 → … |
Internet address |