Argumentation mining is a recent challenge concerning the automatic extraction of arguments from unstructured textual corpora. Argumentation mining technologies are rapidly evolving and show a clear potential for application in diverse areas such as recommender systems, policy-making and the legal domain. There is a long-recognised need for tools that enable users to browse, visualise, search, and manipulate arguments and argument structures. There is, however, a lack of widely accessible tools. In this article we describe the technology behind MARGOT, the first online argumentation mining system designed to reach out to the wider community of potential users of these new technologies. We evaluate its performance and discuss its possible application in the analysis of content from various domains.

Lippi, M., Torroni, P. (2016). MARGOT: A web server for argumentation mining. EXPERT SYSTEMS WITH APPLICATIONS, 65, 292-303 [10.1016/j.eswa.2016.08.050].

MARGOT: A web server for argumentation mining

LIPPI, MARCO;TORRONI, PAOLO
2016

Abstract

Argumentation mining is a recent challenge concerning the automatic extraction of arguments from unstructured textual corpora. Argumentation mining technologies are rapidly evolving and show a clear potential for application in diverse areas such as recommender systems, policy-making and the legal domain. There is a long-recognised need for tools that enable users to browse, visualise, search, and manipulate arguments and argument structures. There is, however, a lack of widely accessible tools. In this article we describe the technology behind MARGOT, the first online argumentation mining system designed to reach out to the wider community of potential users of these new technologies. We evaluate its performance and discuss its possible application in the analysis of content from various domains.
2016
Lippi, M., Torroni, P. (2016). MARGOT: A web server for argumentation mining. EXPERT SYSTEMS WITH APPLICATIONS, 65, 292-303 [10.1016/j.eswa.2016.08.050].
Lippi, Marco; Torroni, Paolo
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/592276
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