Robust Argumentation Machines: First International Conference, RATIO 2024, Bielefeld, Germany, June 5-7, 2024, Proceedings

by Philipp Cimiano (Editor), Anette Frank (Editor), Michael Kohlhase (Editor), Benno Stein (Editor)

Overview

This open access book constitutes the proceedings of the First International Conference on Robust Argumentation Machines, RATIO 2024, which took place in Bielefeld, Germany, during June 5-7, 2024.

The 20 full papers and 1 short paper included in the proceedings were carefully reviewed and selected from 24 submissions. They were organized in topical sections as follows:

Argument Mining; Debate Analysis and Deliberation; Argument Acquisition, Annotation and Quality Assessment; Computational Models of Argumentation; Interactive Argumentation, Recommendation and Personalization; and Argument Search and Retrieval.

Product Details

ISBN-13:	9783031635359
Publisher:	Springer Nature Switzerland
Publication date:	07/17/2024
Series:	Lecture Notes in Computer Science , #14638
Edition description:	2024
Pages:	372
Product dimensions:	6.10(w) x 9.25(h) x (d)

Table of Contents

Argument Mining.- Natural language hypotheses in scientific papers and how to tame them: Suggested steps for formalizing complex scientific claims.- Weakly Supervised Claim Localization in Scientific Abstracts.- Argument Mining of Attack and Support Patterns in Dialogical Conversations with Sequential Pattern Mining.- Cluster-Specific Rule Mining for Argumentation-Based Classification.- Debate Analysis and Deliberation.- Automatic Analysis of Political Debates and Manifestos: Successes and Challenges.- PAKT: Perspectivized Argumentation Knowledge Graph and Tool for Deliberation Analysis.- PolArg: Unsupervised Polarity Prediction of Arguments in Real-Time Online Conversations.- Argument Acquisition, Annotation and Quality.- Assessment Are Large Language Models Reliable Argument Quality Annotators.- The Impact of Argument Arrangement on Essay Scoring.- Finding Argument Fragments on Social Media with Corpus Queries and LLMs.- Computational Models of Argumentation.- Enhancing Abstract Argumentation Solvers with Machine Learning-Guided Heuristics: A Feasibility Study.- Ranking Transition-based Medical Recommendations using Assumption-based Argumentation.- Argumentation-based Probabilistic Causal Reasoning.- From Networks to Narratives: Bayes Nets and the problems of argumentation.- Enhancing Argument Generation using Bayesian Networks.- “Do not disturb my circles!” Identifying the Type of Counterfactual at Hand.- Interactive Argumentation, Recommendation and Personalization.- BEA: Building Engaging Argumentation.- Deciphering Personal Argument Styles – A Comprehensive Approach to Analyzing Linguistic Properties of Argument Preferences.- Argument Search and Retrieval.- Extending the Comparative Argumentative Machine: Multilingualism and Stance Detection.- Objective Argument Summarization in Search.- ArgServices: A Microservice-Based Architecture for Argumentation Machines.