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Neural-Symbolic Argumentation Mining: An Argument in Favor of Deep Learning and Reasoning

Galassi, Andrea ; Kersting, Kristian ; Lippi, Marco ; Shao, Xiaoting ; Torroni, Paolo (2024)
Neural-Symbolic Argumentation Mining: An Argument in Favor of Deep Learning and Reasoning.
In: Frontiers in Big Data, 2020, 2
doi: 10.26083/tuprints-00016123
Article, Secondary publication, Publisher's Version

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Item Type: Article
Type of entry: Secondary publication
Title: Neural-Symbolic Argumentation Mining: An Argument in Favor of Deep Learning and Reasoning
Language: English
Date: 8 March 2024
Place of Publication: Darmstadt
Year of primary publication: 22 January 2020
Place of primary publication: Lausanne
Publisher: Frontiers Media S.A.
Journal or Publication Title: Frontiers in Big Data
Volume of the journal: 2
Collation: 6 Seiten
DOI: 10.26083/tuprints-00016123
Corresponding Links:
Origin: Secondary publication DeepGreen
Abstract:

Deep learning is bringing remarkable contributions to the field of argumentation mining, but the existing approaches still need to fill the gap toward performing advanced reasoning tasks. In this position paper, we posit that neural-symbolic and statistical relational learning could play a crucial role in the integration of symbolic and sub-symbolic methods to achieve this goal.

Uncontrolled Keywords: neural symbolic learning, argumentation mining, probabilistic logic programming, integrative AI, DeepProbLog, Ground-Specific Markov Logic Networks
Identification Number: Artikel-ID: 52
Status: Publisher's Version
URN: urn:nbn:de:tuda-tuprints-161235
Additional Information:

Specialty section: This article was submitted to Machine Learning and Artificial Intelligence, a section of the journal Frontiers in Big Data

Classification DDC: 000 Generalities, computers, information > 004 Computer science
Divisions: 20 Department of Computer Science > Artificial Intelligence and Machine Learning
Zentrale Einrichtungen > Centre for Cognitive Science (CCS)
Date Deposited: 08 Mar 2024 13:21
Last Modified: 06 Jun 2024 14:02
SWORD Depositor: Deep Green
URI: https://tuprints.ulb.tu-darmstadt.de/id/eprint/16123
PPN: 518878279
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