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Record Nr. |
UNINA9910874688403321 |
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Autore |
Cimiano Philipp |
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Titolo |
Robust Argumentation Machines : First International Conference, RATIO 2024, Bielefeld, Germany, June 5–7, 2024, Proceedings / / edited by Philipp Cimiano, Anette Frank, Michael Kohlhase, Benno Stein |
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Pubbl/distr/stampa |
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Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024 |
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ISBN |
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Edizione |
[1st ed. 2024.] |
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Descrizione fisica |
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1 online resource (379 pages) |
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Collana |
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Lecture Notes in Artificial Intelligence, , 2945-9141 ; ; 14638 |
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Altri autori (Persone) |
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FrankAnette |
KohlhaseMichael |
SteinBenno |
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Disciplina |
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Soggetti |
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Artificial intelligence |
Computer science |
Logic programming |
Logic, Symbolic and mathematical |
Machine theory |
Software engineering |
Artificial Intelligence |
Theory of Computation |
Logic in AI |
Mathematical Logic and Foundations |
Formal Languages and Automata Theory |
Software Engineering |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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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 |
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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. |
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Sommario/riassunto |
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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. . |
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