Towards neuro-argumentative agents based on the seamless integration of neural networks and defeasible formalisms, with principled probabilistic settings and along efficient algorithms, we investigate argumentative Boltzmann machines where the possible states of a Boltzmann machine are constrained by a prior argumentative knowledge. To make our ideas as widely applicable as possible, and acknow...

Scoring the quality of persuasive essays is an important goal of discourse analysis, addressed most recently with highlevel persuasion-related features such as thesis clarity, or opinions and their targets. We investigate whether argumentation features derived from a coarse-grained argumentative structure of essays can help predict essays scores. We introduce a set of argumentation features rel...

An agent aims to secure his projected needs by attempting to build a set of (business) relationships with other agents. A relationship is built by exchanging private information, and is characterised by its intimacy — degree of closeness — and balance — degree of fairness. Each argumentative interaction between two agents then has two goals: to satisfy some immediate need, and to do so in a way...

Argumentation mining is considered as a key technology for future search engines and automated decision making. In such applications, argumentative text segments have to be mined from large and diverse document collections. However, most existing argumentation mining approaches tackle the classification of argumentativeness only for a few manually annotated documents from narrow domains and reg...

We propose a novel factor graph model for argument mining, designed for settings in which the argumentative relations in a document do not necessarily form a tree structure. (This is the case in over 20% of the web comments dataset we release.) Our model jointly learns elementary unit type classification and argumentative relation prediction. Moreover, our model supports SVM and RNN parametriza...

An agent aims to secure his projected needs by attempting to build a set of (business) relationships with other agents. A relationship is built by exchanging private information, and is characterised by its intimacy — degree of closeness — and balance — degree of fairness. Each argumentative interaction between two agents then has two goals: to satisfy some immediate need, and to do so in a way...

Defeasible argumentation is one of the approaches that attempt to address the challenges arising when we reason defeasibly, with several formalisms in the literature reaching a mature state. Nowadays, several of them started shifting their semantics towards a dialectical characterization. Therefore, we believe that a sufficiently generic model of the process of dialectical reasoning could also ...

We present a maximum entropy classifier that significantly improves the accuracy of Argumentative Zoning in scientific literature. We examine the features used to achieve this result and experiment with Argumentative Zoning as a sequence tagging task, decoded with Viterbi using up to four previous classification decisions. The result is a 23% F-score increase on the Computational Linguistics co...

We report on the development of a new automatic feedback model to improve information retrieval in digital libraries. Our hypothesis is that some particular sentences, selected based on argumentative criteria, can be more useful than others to perform well-known feedback information retrieval tasks. The argumentative model we explore is based on four disjunct classes, which has been very regula...

PROBLEM Automatic keyword assignment has been largely studied in medical informatics in the context of the MEDLINE database, both for helping search in MEDLINE and in order to provide an indicative "gist" of the content of an article. Automatic assignment of Medical Subject Headings (MeSH), which is formally an automatic text categorization task, has been proposed using different methods or com...