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.

Lippi, M., Torroni, P. (2015). Argument Mining: A Machine Learning Perspective. Springer International Publishing [10.1007/978-3-319-28460-6_10].

Argument Mining: A Machine Learning Perspective

LIPPI, MARCO;TORRONI, PAOLO
2015

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.
2015
Theory and Applications of Formal Argument. Third International Workshop, TAFA 2015, Buenos Aires, Argentina, July 25-26, 2015, Revised Selected Papers
163
176
Lippi, M., Torroni, P. (2015). Argument Mining: A Machine Learning Perspective. Springer International Publishing [10.1007/978-3-319-28460-6_10].
Lippi, Marco; Torroni, Paolo
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/525158
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