Developing a Conversational Agent’s Capability to Identify Structural Wrongness in Arguments Based on Toulmin’s Model of Arguments

This article discusses the usefulness of Toulmin’s model of arguments as structuring an assessment of different types of wrongness in an argument. We discuss the usability of the model within a conversational agent that aims to support users to develop a good argument. Within the article, we present a study and the development of classifiers that identify the existence of structural components in a good argument, namely a claim, a warrant (underlying understanding), and evidence. Based on a dataset (three sub-datasets with 100, 1,026, 211 responses in each) in which users argue about the intelligence or non-intelligence of entities, we have developed classifiers for these components: The existence and direction (positive/negative) of claims can be detected a weighted average F1 score over all classes (positive/negative/unknown) of 0.91. The existence of a warrant (with warrant/without warrant) can be detected with a weighted F1 score over all classes of 0.88. The existence of evidence (with evidence/without evidence) can be detected with a weighted average F1 score of 0.80. We argue that these scores are high enough to be of use within a conditional dialogue structure based on Bloom’s taxonomy of learning; and show by argument an example conditional dialogue structure that allows us to conduct coherent learning conversations. While in our described experiments, we show how Toulmin’s model of arguments can be used to identify structural problems with argumentation, we also discuss how Toulmin’s model of arguments could be used in conjunction with content-wise assessment of the correctness especially of the evidence component to identify more complex types of wrongness in arguments, where argument components are not well aligned. Owing to having progress in argument mining and conversational agents, the next challenges could be the developing agents that support learning argumentation. These agents could identify more complex type of wrongness in arguments that result from wrong connections between argumentation components.

e-Commerce Online Intelligent Customer Service System Based on Fuzzy Control

In order to improve the intelligence of the e-commerce online intelligent customer service system, this paper proposes a deep rejection recognition algorithm based on the maximum interval squared hinge loss and combines the actual needs of the e-commerce online customer service system to build an intelligent customer service system with the support of the fuzzy control system. Moreover, this article chooses to build a domain ontology library for structured storage of domain knowledge needed by customer service chatbots. In addition, this article analyzes the dialogue structure based on the speech act model and combines the semantic vector model of the question sentence on the basis of the dialogue structure to understand the question sentence, which helps to improve the accuracy of the answer feedback of the Internet shopping customer service robot. Finally, this article designs experiments to verify the performance of the online customer service system constructed in this article and analyzes the experimental results through statistical methods. The experimental results show that the online intelligent customer service system constructed in this paper has certain practical effects.

A Dostoevskian Dialogue Structure for the Presentation of the Unconscious

In this article, I demonstrate that in Crime and Punishment (1866) and Demons (1872), Dostoevsky uses a specific type of dialogue—which I term “the about-face dialogue”—to present the displacement of a young man’s unconscious rage against his mother on to society while hiding it from the awareness of both protagonist and reader. In this type of dialogue, the protagonist interprets his interlocutor’s unwittingly ambiguous word or phrase as a scathing rebuke of his rage against his mother, and his reaction constitutes a displacement of this rage on to the outside world. Our awareness of the interplay between the unconscious and the outside world in this type of dialogue enables us to understand the protagonist’s sudden about-face from compassion to apathy, or even animosity, which is incomprehensible on the purely rational level.

Les principales orientations de la réforme de la PAC post 2020

Cet article présente les principales orientations de la réforme de la politique agricole commune (PAC) proposée par la Commission Européenne pour l’après 2020. Cette réforme s’appuie sur une analyse de la PAC actuelle, affirme la volonté de mieux prendre en compte les défis climatiques et environnementaux et propose une révision de la gouvernance. Il en résulte une articulation plus étroite entre les deux piliers, une mise en cohérence avec les autres politiques environnementales et climatiques, ainsi que des principes de flexibilité dans la conception des actions, une approche tournée vers la recherche de performances et un meilleur suivi de l’évaluation des impacts. Cette réforme a fait l’objet d’un dialogue structuré avec les états-membres, en particulier dans la préparation de plans stratégiques nationaux et s’intégrer dans la mise en œuvre du pacte vert de la Commission.

Managing the Complexity of Dialogues in Context: A Data-Driven Discovery Method for Dialectical Reply Structures

Current formal dialectical models postulate normative rules that enable discussants to conduct dialogical interactions without committing fallacies. Though the rules for conducting a dialogue are supposed to apply to interactions between actual arguers, they are without exception theoretically motivated. This creates a gap between model and reality, because dialogue participants typically leave important content-related elements implicit. Therefore, analysts cannot readily relate normative rules to actual debates in ways that will be empirically confirmable. This paper details a new, data-driven method for describing discussants’ actual reply structures, wherein corpus studies serve to acknowledge the complexity of natural argumentation (itself understood as a function of context). Rather than refer exclusively to propositional content as an indicator of arguing pro/contra a given claim, the proposed approach to dialogue structure tracks the sequence of dialogical moves itself. This arguably improves the applicability of theoretical dialectical models to empirical data, and thus advances the study of dialogue systems.

Examining Transactional Distance in Synchronous Online Learning Environments

Even though there have been many studies focused on different points of transactional distance (TD) and it has been measured in different ways, it needs to be further assessed using different distance learning contexts to understand the interaction of the constructs. The purpose of this study was to investigate the level of association among dialogue, structure, and learner autonomy components and TD and to examine the effects of these components on satisfaction and perceived learning of distance learners in Turkey. The results of this study indicated a negative significant correlation between dialogue and TD and a positive significant correlation between TD and course delivery, which is one of the sub-components of the structure. Results of the study indicated TD was negatively related with satisfaction and perceived learning as expected. The current study intended to contribute to the operational definition of TD and to contribute to the field of distance education by providing a unique experience from a national context.