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.

Argument mining: A machine learning perspective / Lippi, Marco; Torroni, Paolo. - 9524(2015), pp. 163-176. ((Intervento presentato al convegno 3rd International Workshop on Theory and Applications of Formal Argumentation, TAFA 2015 tenutosi a Buenos Aires; Argentina nel July 25-26, 2015.

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