Results 1 to 10 of about 369,727 (288)

Fusion weighted features and BiLSTM-attention model for argument mining of EFL writing [PDF]

open access: yesFrontiers in Psychology, 2023
Argument mining (AM), an emerging field in natural language processing (NLP), aims to automatically extract arguments and the relationships between them in texts. In this study, we propose a new method for argument mining of argumentative essays.
Jincai Yang, Meng Zheng, Yingliang Liu
doaj   +2 more sources

Performance analysis of large language models in the domain of legal argument mining [PDF]

open access: yesFrontiers in Artificial Intelligence, 2023
Generative pre-trained transformers (GPT) have recently demonstrated excellent performance in various natural language tasks. The development of ChatGPT and the recently released GPT-4 model has shown competence in solving complex and higher-order ...
Abdullah Al Zubaer   +3 more
doaj   +2 more sources

Argument mining as rapid screening tool of COVID-19 literature quality: Preliminary evidence [PDF]

open access: yesFrontiers in Public Health, 2022
BackgroundThe COVID-19 pandemic prompted the scientific community to share timely evidence, also in the form of pre-printed papers, not peer reviewed yet.PurposeTo develop an artificial intelligence system for the analysis of the scientific literature by
Gianfranco Brambilla   +9 more
doaj   +2 more sources

Argument Mining: A Survey [PDF]

open access: yesComputational Linguistics, 2020
Argument mining is the automatic identification and extraction of the structure of inference and reasoning expressed as arguments presented in natural language.
Lawrence, John, Reed, Chris
doaj   +3 more sources

Argument Mining Using Argumentation Scheme Structures [PDF]

open access: yes, 2016
Argumentation schemes are patterns of human reasoning which have been detailed extensively in philosophy and psychology. In this paper we demonstrate that the structure of such schemes can provide rich information to the task of automatically identify ...
Lawrence, John, Reed, Chris
core   +5 more sources

Research Advances in Argument Mining [PDF]

open access: yesNongye tushu qingbao xuebao, 2023
[Purpose/Significance] Argument mining, a research hotspot in the field of computational linguistics, provides machine processable structured data for computational models of argument. Argument mining tasks are closely related to artificial intelligence (
LI Jiao, ZHAO Ruixue, XIAN Guojian, HUANG Yongwen, SUN Tan
doaj   +2 more sources

Argument mining: A machine learning perspective [PDF]

open access: yes, 2015
Argument mining has recently become a hot topic, attracting the interests of several and diverse research communities, ranging from artificial intelligence, to computational linguistics, natural language processing, social and philosophical sciences.
A Peldszus   +22 more
core   +5 more sources

RuArg-2022: Argument Mining Evaluation

open access: yesComputational Linguistics and Intellectual Technologies, 2022
Argumentation analysis is a field of computational linguistics that studies methods for extracting arguments from texts and the relationships between them, as well as building argumentation structure of texts. This paper is a report of the organizers on the first competition of argumentation analysis systems dealing with Russian language texts within ...
Kotelnikov E   +3 more
europepmc   +3 more sources

Perception and argumentation in the LK-99 superconductivity controversy: a sentiment and argument mining analysis [PDF]

open access: yesScientific Reports
The announcement of LK-99 as a potential room-temperature, ambient-pressure superconductor sparked widespread debate across both traditional news outlets and social media platforms.
Eunhye Kim, Wei Luo, Hunkoog Jho
doaj   +2 more sources

Argumentation Mining in User-Generated Web Discourse

open access: yesComputational Linguistics, 2016
The goal of argumentation mining, an evolving research field in computational linguistics, is to design methods capable of analyzing people's argumentation. In this article, we go beyond the state of the art in several ways.
Ivan Habernal, Iryna Gurevych
doaj   +2 more sources

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