Publicação

Applying machine learning classifiers in argumentation context

Detalhes bibliográficos
Resumo:	Group decision making is an area that has been studied over the years. Group Decision Support Systems emerged with the aim of supporting decision makers in group decision-making processes. In order to properly support decision-makers these days, it is essential that GDSS provide mechanisms to properly support decision-makers. The application of Machine Learning techniques in the context of argumentation has grown over the past few years. Arguing includes negotiating arguments for and against a certain point of view. From political debates to social media posts, ideas are discussed in the form of an exchange of arguments. During the last years, the automatic detection of this arguments has been studied and it’s called Argument Mining. Recent advances in this field of research have shown that it is possible to extract arguments from unstructured texts and classifying the relations between them. In this work, we used machine learning classifiers to automatically classify the direction (relation) between two arguments.
Autores principais:	Conceição, Luís
Outros Autores:	Carneiro, João; Marreiros, Goreti; Novais, Paulo
Assunto:	Argument mining Argumentation-based dialogues Machine learning classifiers
Ano:	2021
País:	Portugal
Tipo de documento:	comunicação em conferência
Tipo de acesso:	acesso restrito
Instituição associada:	Universidade do Minho
Idioma:	inglês
Origem:	RepositóriUM - Universidade do Minho

Descrição
Resumo:	Group decision making is an area that has been studied over the years. Group Decision Support Systems emerged with the aim of supporting decision makers in group decision-making processes. In order to properly support decision-makers these days, it is essential that GDSS provide mechanisms to properly support decision-makers. The application of Machine Learning techniques in the context of argumentation has grown over the past few years. Arguing includes negotiating arguments for and against a certain point of view. From political debates to social media posts, ideas are discussed in the form of an exchange of arguments. During the last years, the automatic detection of this arguments has been studied and it’s called Argument Mining. Recent advances in this field of research have shown that it is possible to extract arguments from unstructured texts and classifying the relations between them. In this work, we used machine learning classifiers to automatically classify the direction (relation) between two arguments.