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  1. Research Outputs

Argument mining: A machine learning perspective

Conference Paper
Publication Date:
2015
Short description:
Argument mining: A machine learning perspective / Lippi, Marco; Torroni, Paolo. - 9524:(2015), pp. 163-176. ( 3rd International Workshop on Theory and Applications of Formal Argumentation, TAFA 2015 Buenos Aires; Argentina July 25-26, 2015) [10.1007/978-3-319-28460-6_10].
abstract:
Argument mining has recently become a hot topic, attracting the interests of several and diverse research communities, ranging from artificial intelligence, to computational linguistics, natural language processing, social and philosophical sciences. In this paper, we attempt to describe the problems and challenges of argument mining from a machine learning angle. In particular, we advocate that machine learning techniques so far have been under-exploited, and that a more proper standardization of the problem, also with regards to the underlying argument model, could provide a crucial element to develop better systems.
Iris type:
Relazione in Atti di Convegno
Keywords:
Computer Science (all); Theoretical Computer Science
List of contributors:
Lippi, Marco; Torroni, Paolo
Handle:
https://iris.unimore.it/handle/11380/1122661
Book title:
Theory and Applications of Formal Argumentation
Published in:
LECTURE NOTES IN COMPUTER SCIENCE
Journal
LECTURE NOTES IN COMPUTER SCIENCE
Series
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